Authentication Protocols for Internet of Things: A ...downloads.hindawi.com/journals/scn/2017/6562953.pdf · Internet will consist of over 50 billion connected things, including sensors,

Review ArticleAuthentication Protocols for Internet of ThingsA Comprehensive Survey

Mohamed Amine Ferrag12 Leandros A Maglaras3 Helge Janicke3

Jianmin Jiang4 and Lei Shu56

1Department of Computer Science Guelma University BP 401 24000 Guelma Algeria2Networks and Systems Laboratory Badji Mokhtar University BP 12 23000 Annaba Algeria3School of Computer Science and Informatics Cyber Security Centre De Montfort University Leicester UK4Research Institute for Future Media Computing Shenzhen University Shenzhen China5Guangdong University of Petrochemical Technology Guangdong China6School of Engineering University of Lincoln Lincoln UK

Correspondence should be addressed to Leandros A Maglaras leandrosmaggmailcom

Received 27 April 2017 Accepted 28 September 2017 Published 6 November 2017

Academic Editor Mahmoud Ghorbel

Copyright copy 2017 Mohamed Amine Ferrag et alThis is an open access article distributed under theCreativeCommonsAttributionLicense which permits unrestricted use distribution and reproduction in anymedium provided the originalwork is properly cited

In this paper a comprehensive survey of authentication protocols for Internet of Things (IoT) is presented Specifically more thanforty authentication protocols developed for or applied in the context of the IoT are selected and examined in detailThese protocolsare categorized based on the target environment (1) Machine to Machine Communications (M2M) (2) Internet of Vehicles (IoV)(3) Internet of Energy (IoE) and (4) Internet of Sensors (IoS) Threat models countermeasures and formal security verificationtechniques used in authentication protocols for the IoT are presented In addition a taxonomy and comparison of authenticationprotocols that are developed for the IoT in terms of networkmodel specific security goals main processes computation complexityand communication overhead are provided Based on the current survey open issues are identified and future research directionsare proposed

1 Introduction

The forecasters believe that the Internet of Things (IoT)holds great promise for many life-improving applicationsAccording to forecasts from Cisco Systems [1] by 2020 theInternet will consist of over 50 billion connected thingsincluding sensors actuators GPS devices mobile devicesand all smart things that can be envisioned in the futureCurrently IBM has decided to combine several products andservices into a product called IoT Solutions Practice [2] toallow the customers to find all IBM IoT offers at the samelocation For example IBM offers the Watson IoT platform[3] which combines scanning security and blockchaintechnology for authentication with a set of APIs such asIBMrsquos SoftLayer cloud infrastructure [4] The IoT can berealized under three scopes namely Internet-oriented (mid-dleware) things-oriented (sensors) and semantic-oriented(knowledge) [5] According to Atzori et al [6] IoT can be

represented as a three-layered architectural model whichconsists of the application layer the network layer and thesensing layer

As shown in Figure 1 IoT has made its entrance in fourfields including (1) Machine to Machine Communications(M2M) (2) Internet of Vehicles (IoV) (3) Internet of Energy(IoE) and (4) Internet of Sensors (IoS) M2M is a technologycrucial for the realization of IoT which is based on differentprotocols such as the protocol Stack [7] The IoV is basedon the concept of Vehicular Cloud which offers access tothe Internet and is temporarily created by interconnectingresources available on the vehicles along with Road SideUnits (RSUs) [8ndash10] According to ARTEMIS-project [11]the IoE is the connection of smart grids with the Internetin order to enable intelligent control of energy productionstorage and distribution The IoS refers to the possibility ofconnecting sensors with the Internet using ZigBee and other

HindawiSecurity and Communication NetworksVolume 2017 Article ID 6562953 41 pageshttpsdoiorg10115520176562953

2 Security and Communication Networks

Data owData ow

Pow ow

Smart

E-Vehicle

Hotspot Service

Charging station

Control center (CC)

Control center

Control ow

Vehicle to grid (V2G) networkVehicle to grid

Notations

(V2G) network

Generation

Transmission

Distribution

Customers

Machine

Machine

SCADA system

Socialspot

User

User to user communication

User to socialspot communication

Gateway

Gateway

InternetHttpwww

Internet of Vehicles (IoV)

Internet of Sensors (IoS)

Machine

Machine to Machine Communications (M2M)

Internet of Energy (IoE)

middot middot middot

X

X

Figure 1 Internet of Things (IoT) in four environments including (1) Internet of Vehicles (IoV) (2) Internet of Energy (IoE) (3) Internetof Sensors (IoS) and (4) Machine to Machine Communications (M2M)

IEEE 802154 based protocols [12] The list of acronyms usedin this paper is listed in Acronyms Section

The vision of the IoT will advance based on many newfeatures and will cope with new challenges as shown inFigure 2 including cloud computing M2M IoS IoE IoVsocial networks software defined optical networks (SDONs)and fifth generation (5G) cellular networks The IoT datawhich will be produced from billions of interactions betweendevices and people is going to be not only massive but alsocomplex and it will suffer from many security and privacyproblems especially regarding the authentication amongdevices To resolve these security issues researchers in thefield of computer security have developed many authentica-tion protocols applied in the context of the IoT The aim ofthe current survey paper is to provide a comprehensive and

systematic review of recent studies on published authentica-tion protocols for the IoT in four environments includingM2M IoV IoE and IoS More precisely more than fortyauthentication protocols are selected and examined in detailThe original set of papers was formed from the searchers runon SCOPUS and Web of Science from the period between2010 and 2016The search started on 15102016 and continueduntil the submission date of this paper See Table 1 for abreakdown of publication dates The main contributions ofthis paper are as follows

(i) Previous survey articles published in recent years thatdeal with the IoT are briefly presented

(ii) Authentication protocols in M2M IoV IoE andIoS that were evaluated under thirty-five attacks are

Security and Communication Networks 3

Internet today

Internet of Things (IoT)

Cloud computing





Social networks

Soware Defined OpticalNetworks (SDONs)

Fih generation (5G) cellular networks

Figure 2 Vision of the IoT with main features and challenges

Table 1 Publication date breakdown-surveyed papers (authentica-tion protocols)

Papers Year[17ndash24] 2010[25ndash31] 2011[32ndash36] 2012[37ndash45] 2013[46ndash51] 2014[52ndash60] 2015[61ndash77] 2016

discussed Main focus is given on five attacks whichare mostly studied in earlier works namely man-in-the-middle attack impersonation attack forgingattack replay attack and Sybil attack

(iii) Various countermeasures and formal security verifi-cation techniques used by authentication protocolsfor the IoT are presented

(iv) A side-by-side comparison in a tabular form of thecurrent state-of-the-art of authentication protocolswhich are proposed for the IoT viewed from fivedifferent aspects namely network model specificsecurity goalsmain processes computation complex-ity and communication overhead is given

(v) Open issues forM2M IoV IoE and IoS are discussed

The rest of this paper is organized as follows Section 2summarizes the existing survey works on different aspects ofthe IoT idea In Section 3 an overview of threat models in theIoT is presented Section 4 presents various countermeasuresand formal security verification techniques In Section 5 ataxonomy and comparison of authentication protocols for theIoT is presented Finally open issues and recommendationsfor further research are discussed in Section 6 and mainconclusions are drawn in Section 7

2 Surveys Articles for the IoT

There exist many survey articles published during recentyears that deal with Internet of Things focusing on differentaspects of the IoT idea for example networking applications

standardization social interactions security andmanymoreThese survey articles are categorized in terms of field ofresearch as shown in Table 2 Internet of Things conceptsattracts more and more attention as the years pass by andalthough a lot of different areas related to IoT are coveredfrom previous review works no survey article exists thatthoroughly investigates authentication protocols that areespecially developed for this new technology or better saythis blend of technologies and systems In this section we willbriefly present all these survey articles grouped as shown inTable 2 and will discuss in more depth previous works thatdeal with security and privacy issues of the IoT

The first survey article in the literature that was dealingwith the IoT concept was published back in 2009 by Cooperand James [14] and focused on the challenges for databasemanagement in the IoT Seeing the IoT from that point ofview they found that the technical priorities that neededto be addressed in order to support the interconnection ofevery device were proper indexing archiving developmentof smart agents the use of XML for achieving Interoperabilityand novel systems that will be able to offer efficient and securetransaction management In a later survey article that waspublished in 2010 Atzori et al [6] discussed the vision ofldquoanytime anywhere any media anythingrdquo communicationsthat the IoT would bring in our everyday lives Based ontheir research author spotted two important technologiesthat needed to be applied in order to bring IoT into lifeInternet Protocol version 6 (IPv6) and Web 20 The sameyear the first survey article that dealt with security andprivacy issues related to IoTwas published [15] In this articleWeber discussed the different measures that were needed inorder to ensure the architecturersquos resilience to attacks dataauthentication access control and client privacy The articledealt with security and privacy issues from the legislationperspective mostly due to the fact that the IoT was more anidea back in 2010 than a concrete system yet Another articledealing with security and privacy was published in 2010 fromMedaglia and Serbanati [16] The article tried to present ashort term and a long-term vision of the IoT along with thesecurity issues and solutions that would be needed

In 2011 several published survey articles focused on theIoT [83 87 89 93 104 126] In [87] authors conducted athorough analysis of the different publicly available testbedsBandyopadhyay and Sen [93] published an interesting survey


Table 2 Areas of research of each survey article for the IoT

Ref DD MW AP SE SP Exp Net ST Arch SR RFID Soc DM IIoT[14 78ndash80]

[6 81ndash84]

[6 85 86]

[87]

[7 80 88ndash92]

[93ndash98]

[99ndash103]

[104]

[15 16 89 90 94 105ndash119]

[120 121]

[122ndash125]

[5 6 90 93 94 99 126ndash134]

[135 136]

[100]

DD Data quality and database management MW middleware AP applications SE smart environments SP security and privacy Exp experimentationNet networking ST standardization Arch architecture SR searching RFID RFID technology Soc Social Internet of Things DM data mining and IIoTindustrial Internet of Things

article about the current developments related to IoT and theopen issues back in 2011 The article managed to spot most ofthe challenges that IoT had and still has to face nowadays forexample managing large amount of information and mininglarge volume of data managing heterogeneity and ensuringsecurity privacy and trust among others Feasible solutionsfor the problem of establishing a session key between a clientand a server in the context of the Internet of Things weresurveyed in [89] where the authors considered the scenariowhere at least one peer was a sensor node They especiallyfocused on different cryptography solutions and how thesecould be applied to server and client nodes Ma in [126] gavean overview of the objectives of the IoT and the challengesinvolved in IoT development while in [104] Zhang et alcovered the topic of how to build an appropriate search enginefor IoT a topic that was spotted from Cooper and James in[14] back in 2009 as a challenge to be addressed in the future

During 2012 and 2013 the following survey articles werepublished [5 82 94ndash97 99 105 106 122 123] dealingwith standardization applications architecture security andprivacy issues of the IoT Articles [95ndash97] surveyed stan-dardization issues and how the IETF Constrained RESTfulEnvironments (CoRE) working group focuses on facilitatingthe integration of constrained devices with the Internet atthe service level These articles pointed out that all thestandardized protocols are only a starting point for exploringadditional open issues like resource representation securityand privacy energy efficiency and so on Authors in [5 94]gave a general overview of the current vision applicationsarchitectural elements and future challenges and directionsof the IoT Miorandi et al in [94] discussed the potentialimpact of the IoT on smart home automation smart citiesenvironmental monitoring health care smart businessesand security and surveillance making very clear maybe forthe first time that the IoT concept involves every currentor future technology that is going to be introduced in

order to make our life better Domingo in [99] performeda more narrow but extensive survey of the IoT for peoplewith disabilities Authors spotted the relevant applicationscenarios and main benefits along with the key researchchallenges like customization self-management and secu-rity and privacy issues They argued that as brainndashcomputerinterfaces (BCIs) are becoming commercial they will also bea part of the IoT world Articles [105 106] focused on securityand privacy issues as they were identified back in 2012 and2013 respectively Both articles agree that key managementneeds strong legislation while authors in [106] take one stepfurther and propose that grouping of the IoT devices andcreating the so called intranet of things could help imposesecurity mechanisms more effectively Finally articles [122123] survey for the first time the social concept of the IoT theso called Social Internet of Things a concept that later willraise a lot of attraction and research works

During 2014 and 2015 more than twenty new surveyarticles about IoT were published [7 85 98 100 102 107108 110 112ndash116 121 124 128ndash130 135 136 212 213] Exceptarticles that discussed general issues regarding IoT [98 129130 212] for example applications challenges trends andopen issues other papers focused on specific applications orresearch areas that are connected to the IoT idea Authors inall three articles agree that IoT thus brings new opportunitiesby enabling enriched context-aware services but it also raisesnew challenges that need to be addressed Zanella et al [85]focused specifically to an urban IoT system which is anotherterm to describe the smart city environment In contrast tothe previous years during 2014 and 2015 a big proportionof the survey articles focus on security and privacy issuesrelated to the IoT [107 108 110 112ndash116] revealing thesignificance that security was beginning to have for cyber-physical systems Cyber-Physical systems need to rely on IoTenabled technologies which can be effectively and efficientlysupported and assisted by cloud computing infrastructures


Classication ofattacks in the IoT

(i) Passive attacks(ii) Active attacks

(i) Identity-based attacks(ii) Location-based attacks(iii) Eavesdropping-based attacks(iv) Manipulation-based attacks(v) Service-based attacks

(i) Internal attacks(ii) External attacks

(i) Key-based attacks(ii) Data-based attacks(iii) Impersonation-based attacks(iv) Physical-based attacks

Figure 3 Classification of attacks in the IoT

and platforms The integration of IoT and cloud computingwas thoroughly surveyed from Botta et al [128] where alsothe possibility of exploiting fog computing capabilities forsupporting the IoT concept was discussed Data mining inthe IoT context was surveyed by Tsai et al [135] and Chenet al [136] Authors in [135] presented a good summaryof the potentials that applying data mining technologies tothe IoT could have to people the system itself and otherinterconnected systems Authors in [136] took a step furtherand based on their survey and analysis proposed a big datamining system for IoT Ortiz et al [124] surveyed the SocialInternet ofThings and compared to the earlier survey articles[122 123] proposed a generic SIoT architecturewhich consistsof actors a central intelligent system an interface and theInternet Two articles focused on IoT-based health caretechnologies [121 213] covering new platforms applicationsand security and privacy issues that arise Authors in [100]conducted an extensive literature review about the currentstatus and future research opportunities regarding the use ofIoT in industries the so called Industrial Internet of Things(IIoT) while in [102] authors tried to identify the impact ofthe Internet ofThings (IoT) on Enterprise Systems inmodernmanufacturing

During 2016 over fifteen new survey articles that focusedon the IoT concept were published [78ndash80 84 86 91 103111 117ndash119 125 131 132 134 214] Following the technologydevelopment three of the articles published this year focusedon the integration of the cloud and the IoT the applicationsthe requirements and the security issues that arise from it[117 131 134] Security was also one aspect that was coveredfrom a number of survey articles [117ndash119] Authors in [118]covered several aspects of IoT security for example generaldevices security communication security network securityand application while in [119] mechanisms that reassuresecure routing were investigated In contrast to previousyears surveys published during 2016 covered new areas suchas SDN and virtualization [91] economic and pricing theoryin IoT [80] social Internet of vehicles [125] and data quality[78] Other topics covered from the survey articles weremiddleware [84] data models [79] mobile crowd sensingstrategies [132] the deployment of IoT in smart environments[86] and the main proposed architectures for IoT [103] Xieet al [111] surveyed the security of the Web of Things (WoT)

which is aimed to provide any electronic item (smart cardssensors etc) with a URL

Among the aforementioned surveys the security andprivacy issues that are related to the IoT were thoroughlycovered and analyzed [15 16 89 90 94 105ndash119] As it isshown in Table 3 data authentication and integrity wereonly covered partially from He and Zeadally [121] while therest of the articles did not cover this major security aspectIn this article we tend to survey authentication protocolsfor the IoT in four environments including (1) Machine toMachine communications (M2M) (2) Internet of Vehicles(IoV) (3) Internet of Energy (IoE) and (4) Internet of Sensors(IoS) Based on this thorough analysis open issues andfuture directions are identified that combine both innovativeresearch along with the application through appropriateadaptation of existing solutions from other fields We believethat this study will help researchers focus on the importantaspects of authentication issues in the IoT area and will guidethem towards their future research

3 Threat Models

In this section various threat models in the IoT are discussedThe summary of thirty-five attacks in M2M IoV IoE andIoS and defense protocols are given in Tables 4 5 6 and7 respectively We focus on five attacks which are mostlyused by authors that propose new authentications protocolsfor evaluating their methods namely man-in-the-middleattack impersonation attack forging attack replay attackand Sybil attack Generally the classification of attacks [215ndash218] frequently mentioned in the literature is done using thefollowing four types as shown in Figure 3

(1) Type A Passive or active(2) Type B Internal or external(3) Type C [219] Key-based attacks data-based attacks

impersonation-based attacks and physical-basedattacks

(4) Type D [220] Identity-based attacks location-basedattacks eavesdropping-based attacks manipulation-based attack and service-based attacks

31 Man-in-the-Middle Attack Theman-in-the-middle (MITM)attack is one of the most well known attacks in the IoT With


Table 3 A comparison of related surveys in the literature (surveys on security and privacy for the IoT)

Survey on security andprivacy for the IoT

Privacypreservingschemes

Authenticationprotocols Comments

Weber (2010) [15] 0 X Presented milestones of an adequate legal frameworkfor IoT privacy

Medaglia and Serbanati(2010) [16] 0 X Presented a Short-Term and Long-Term vision for IoT

privacy

Roman et al (2011) [89] X XAnalyzed some key management systems for sensornetworks in the context of the IoT (public keycryptography and preshared keys)

Miorandi et al (2012) [94] 0 X Presented some security challenges in IoT includingData confidentiality Privacy and Trust

Suo et al (2012) [105] X XDiscussed the security requirements in each level forIoT (four key levels ie recognition layer networklayer support layer and application layer)

Aggarwal et al (2013) [90] 0 X Discussed the privacy in data collection and duringdata transmission and sharing

Roman et al (2013) [106] X X Presented the security issues in distributed IoT systems

Yan et al (2014) [107] XSurveyed the privacy-preserving schemes IoTincluding database query scientific computationsintrusion detection and data mining

Jing et al (2014) [108] X X Discussed the security issues and technical solutions inWSNs

Chabridon et al (2014)[109] X Surveyed the state of the art of privacy technology from

the perspective of the IoTZiegeldorf et al [110] X Surveyed the privacy threats and challenges in the IoT

Keoh et al (2014) [112] X X Presented an overview of the efforts in the IETF tostandardize security solutions for the IoT ecosystem

Sicari et al (2015) [113] 0 X Discussed the privacy trust enforcement securemiddleware and mobile security in the IoT

Granjal et al (2015) [114] X 0 Discussed IoT communications and security at thephysical and MAC layers

Sadeghi et al (2015) [115] X X Discussed an introduction to Industrial IoT systemswith the related security and privacy challenges

Nguyen et al (2015) [116] 0 XSurveyed the secure communication protocols for theIoT including asymmetric key schemes and symmetrickey predistribution schemes

He and Zeadally (2015)[121] X 0

Analyzed only the RFID authentication schemes for theIoT in healthcare environment using elliptic curvecryptography

Xie et al (2016) [111] X X Reviewed the security issues for Web of Things

Singh et al (2016) [117] X X Analyzed the state of cloud-supported IoT to makeexplicit the security considerations

Li et al (2016) [118] X X Analyzed the security requirements and potentialthreats in a four-layer architecture for the IoT

Airehrour et al (2016) [119] X X Analyzed the security of routing protocols for the IoT

Our work 0

Surveyed the authentication protocols for the IoT infour environments including (1)Machine to MachineCommunications (M2M) (2) Internet of Vehicles(IoV) (3) Internet of Energy (IoE) and (4) Internet ofSensors (IoS)

indicates fully supported X indicates not supported 0 indicates partially supported


Table 4 Summary of attacks in Machine to Machine Communications (M2M) and defense protocols

Adversary model Authentication protocols for M2M[62] [61] [46] [38] [34] [53] [47] [137] [37]

Audio replay attack 0 X 0 0 0 X X 0Changing distance attack X X X X X X X XSame-type-device attack X X X X X X X XComposition attack X X X X X X X XRedirection attack 0 0 X X 0 X

Man-in-the-middle attack 0 0 0 0 X X

Substitution attack 0 0 0 0 0 X X X XDoS attack X X X X X XReplay attack 0 X X 0 X X

Forging attack X X X 0 X X X X XColluding attack 0 X X 0 X X 0 X XFlooding attack 0 X X X X X 0 X 0Side-channel attack 0 X X X X X 0 X 0False messages attack 0 X X X 0 0 0 X 0Sybil attack X X X X 0 0 X X 0Movement tracking X X X X 0 X X X 0Message modification X X X X 0 X X X XImpersonation attack X X X X 0 X XGuessing attack X X X X X X X XStolen-verifier attack X X X X X X X XWormhole attack 0 0 X 0 X 0 X X 0Blackhole attack 0 0 X 0 0 0 X X 0Attribute-trace attack X X X X 0 X X X XEavesdropping attack X X X X 0 0 X X 0Chosen-plaintext attack X X X X 0 X X X 0Spam attack 0 X X X 0 0 X X 0Identity theft attack 0 X X X X 0 X X XUser manipulation attack 0 X X X X 0 0 X 0Routing attack 0 X X X X 0 X X XLinkability attack 0 X X X X X X X XRejection attack X X X X X X X X XSuccessive-response attack X X X X X X X X XPacket analysis attack X 0 X X X 0 X X 0Packet tracing attack X 0 X X X 0 X X 0Brute-force attack 0 0 X 0 0 X 0 0 X indicates fully supported X indicates not supported 0 indicates partially supported

MITM attack an adversary can spoof the identities of twohonest nodes (N1 and N2) involved in a network exchangeand pass N1 for N2 and vice versa that is taking controlof the communication channel between N1 and N2 Underthis control an adversary can intercept modify change orreplace target victimsrsquo communication traffic However wenote here that there is a good survey article published in2016 by Conti et al in [13] which presents a comprehensivesurvey on MITM attacks Specifically authors in [13] classifyMITMattacks in three different categories namely (1)MITMbased on impersonation techniques (2) MITM based onthe communication channel and (3) MITM based on thelocation of an adversary As presented in Figure 4 at any

moment an adversary can set up a connection between FalseBTS and Legitimate MS where False MS impersonates thevictimrsquos MS to the real network by resending the identityinformation Moreover as presented in Table 8 there aretwelve authentication protocols for the IoT which can detectand avoid the MITM attack The four authentication proto-cols in [61 75 77 146] use the idea of mutual authenticationThe two authentication protocols [37 38] use the idea ofauthentication acknowledgement phase With the protocol[139] all packets are fully encrypted with the receiverrsquos publickey which can prevent the MITM attack On the other handwith the protocol [39] when the keys generated at the mobilerouter and the relay router for authentication are based on


Table 5 Summary of attacks in Internet of Vehicles (IoV) and defense protocols

Adversary model Authentication protocols for IoV[39] [40] [63] [64] [65] [66] [48] [52] [54]

Audio replay attack 0 0 0 X 0 0 X 0 XChanging distance attack X X X X X X X X XSame-type-device attack X X X X X X X X XComposition attack X X X X X X X X XRedirection attack 0 0 X X X X X X XMan-in-the-middle attack 0 0 X X 0 X XSubstitution attack 0 0 0 X X 0 X XDoS attack X X X X XReplay attack X 0 0 0 0Forging attack 0 X X X 0 X X XColluding attack 0 X 0 X X X X XFlooding attack X X X 0 X X X X XSide-channel attack X X X 0 X X X XFalse messages attack X X X X X X X 0Sybil attack 0 X X X 0 X X 0Movement tracking X X X X X X X XMessage modification X X X X X X 0 XImpersonation attack X X X X X X 0 XGuessing attack X X X X X X X X 0Stolen-verifier attack X X X X X X X X 0Wormhole attack 0 0 X X 0 X 0 0 0Blackhole attack 0 0 X X 0 X 0 0 0Attribute-trace attack X X X X X 0 X X 0Eavesdropping attack X X 0 0 0 X X 0 0Chosen-plaintext attack X X X 0 X X 0 X 0Spam attack X X X 0 X 0 0 X XIdentity theft attack X X X 0 X X 0 X XUser manipulation attack X X X 0 X X 0 0 XRouting attack 0 X 0 X 0 X 0 0 0Linkability attack X X X X X 0 X 0 XRejection attack X X X X X 0 X 0 0Successive-response attack X X X X X 0 X X XPacket analysis attack 0 0 X X 0 0 X 0 0Packet tracing attack 0 0 X X 0 0 X 0 0Brute-force attack X X X X X 0 X 0 0 indicates fully supported X indicates not supported 0 indicates partially supported

the concept of symmetric polynomials an adversary can notidentify a shared key between two legitimate users makingit impossible for him to impersonate a mobile router or arelay router In addition both protocols [72 142] are based ona password and biometric update phase in order to preventan adversary from impersonating the passwords of a smartmeter

32 Impersonation and Forging Attack Under the imper-sonation and forging attack in the IoS an adversary caneavesdrop or intercept the login request message of previoussessions over the publicopen channel during authenticationprotocol execution After that he can modify and retransmit

the message to the user in order to impersonate as a validuser as defined by Amin and Biswas [70] and shown inthe Figure 5 We note that this attack is analyzed more inauthentication protocols that are produced for the IoS More-over as presented in Table 9 there are sixteen authenticationprotocols for the IoT which can detect the impersonation andforging attack The protocol [40] uses two ideas namely (1)linear search algorithm and (2) binary search algorithm Theprotocol [47] uses strong anonymous access authenticationand user tracking on a disputed access request to preventthe impersonation and forging attack Besides the idea ofusing a password for detecting the impersonation of thegateway node is presented by four authentication protocols


Table 6 Summary of attacks in Internet of Energy (IoE) and defense protocols

Adversary model Authentication protocols for IoE[28] [49] [138] [139] [140] [141] [142] [55] [67]

Audio replay attack X X X X X X X X XChanging distance attack 0 X X X X 0 0 0 XSame-type-device attack X X X 0 X X X X XComposition attack X X X X X X X X XRedirection attack X X X 0 X 0 X X XMan-in-the-middle attack 0 0 0 0 0 0 0Substitution attack X 0 X X X X 0 0 XDoS attack X X 0 X 0 X 0Replay attack 0 0 0

Forging attack 0 0 0 0 X X X XColluding attack X 0 X 0 0 X 0 0 XFlooding attack X 0 X 0 X X 0 0 0Side-channel attack X X X X X 0 0 0 XFalse messages attack 0 0 0 0 0 0 0

Sybil attack 0 0 0 0 0 0 X X 0Movement tracking 0 X X X X 0 X X 0Message modification 0 0 0 0 0 0 0

Impersonation attack 0 0 X X 0 X 0 0 0Guessing attack X 0 X 0 X X X X XStolen-verifier attack X X X X X X X X XWormhole attack X X 0 X X 0 0 0 0Blackhole attack X X 0 X X 0 0 0 0Attribute-trace attack X X X 0 X 0 X X XEavesdropping attack 0 0 0 0 0 0 0 0 0Chosen-plaintext attack X X X 0 X X X XSpam attack X X X 0 X X X X XIdentity theft attack X X 0 0 0 X 0 0 0User manipulation attack X X X X 0 X X X 0Routing attack X X 0 0 X X X X XLinkability attack 0 X 0 0 X X 0 0 XRejection attack 0 X 0 0 0 X 0 0 0Successive-response attack 0 X X 0 X X X X 0Packet analysis attack 0 0 0 0 X 0 0

Packet tracing attack 0 0 X 0 0 0 0 0 0Brute-force attack X X X X X 0 X indicates fully supported X indicates not supported 0 indicates partially supported

[53 77 147 148] In addition the hash mechanism which isapplied on the shared key between gateway wireless node andsensors can prevent the impersonation of a sensor

33 Replay Attack The replay attacks are MITM attackswhich consist of intercepting data packets and retransmittingthem as is (without any decryption) to the destination serveras shown in Figure 6 (intercepting D3 and retransmitting it)Under this attack an adversary can obtain the same rightsas the user A wormhole attack can be launched through thereplay attack as shown in Figure 7 However there are twenty-four authentication protocols for the IoT which can detectand avoid the replay attack as presented in Table 10 These

authentication protocols use three ideas namely TimestampHash function and random numbers The idea of randomnumbers is used by [37ndash39 53] The idea of hash function isused by protocols [49 143] such as the IPSec protocol whichimplements an antireplay mechanism based on messageauthentication code (MAC) [221] In addition the idea ofTimestamp in the encrypted messages is used by [40 49 5263 67 68 70 72 73 75ndash77 139ndash144 148]

34 Sybil Attack With the Sybil attack a malicious nodecan claim different identities in order to gain an advantageover legitimate nodes as shown in Figure 8 Based on themember secrets generation stage Zhang et al [65] proposed


Table 7 Summary of attacks in Internet of Sensors (IoS) and defense protocols

Adversary model Authentication protocols for IoS[68] [69] [143] [70] [71] [72] [73] [74] [75] [144] [76] [145] [77] [146] [147] [148]

Audio replay attack X X X X X X X X X X X X X X X XChanging distance attack 0 X 0 X X X X X X X X X X X X XSame-type-device attack 0 X 0 X X X X X 0 X X X X X X XComposition attack 0 X X 0 0 X 0 0 X X X 0 0 0 0Redirection attack 0 0 0 X 0 0 0 0 0 0 0 0 0 0 0Man-in-the-middle attack 0 0 0 0 0 0 0 0 0 0 0Substitution attack 0 X X X X X 0 X 0 0 0 0 0 X X XDoS attack 0 0 0 X 0 X 0 X 0 0 X 0 0 0 0Replay attack 0 0 0 X 0 0

Forging attack 0 0 X 0 0 0 0 0 0 X 0 0Colluding attack 0 0 0 X 0 0 0 X 0 0 0 0 0 0 0Flooding attack 0 X X 0 0 0 X 0 0 0 0 0 0 0 0Side-channel attack X 0 X X X X X X X X X X 0 X X XFalse messages attack 0 X 0 0 0 0 0 0 0 0 0 0 0 0 0 0Sybil attack 0 0 0 X X X 0 0 0 0 0 0 0 0 0Movement tracking 0 0 X X 0 X X 0 0 0 0 0 0 0 0 0Message modification 0 0 0 0 0 0 0 0 0 0 0 0 0 0Impersonation attack 0 0 0 0 X 0 0

Guessing attack 0 0 0 0 0 0 X 0 0Stolen-verifier attack X X 0 0 X X X 0 0 0 0 0 0Wormhole attack 0 0 0 0 0 0 0 X X X X X 0 X X XBlackhole attack 0 0 0 0 0 0 0 X X X X X 0 X X XAttribute-trace attack X X X X X 0 X X 0 X X X 0 X X XEavesdropping attack 0 0 0 0 0 0 0 X 0 0 0 0 0 0 0 0Chosen-plaintext attack X X X X X X X X X X X X X 0 0 0Spam attack X X X 0 X X 0 X 0 X X X X 0 0 0Identity theft attack 0 0 0 X X X 0 X 0 X X X 0 0 0 0User manipulation attack 0 0 X 0 0 X 0 0 0 0 0 0 0 0 0 0Routing attack 0 0 0 0 0 X 0 X 0 X X X 0 X X XLinkability attack 0 0 0 0 0 0 0 X 0 X X X 0 X X XRejection attack 0 0 0 0 0 X 0 X 0 X X X 0 X X XSuccessive-response attack X 0 X 0 X X X 0 X X X X X X XPacket analysis attack 0 0 X 0 0 X X X X X X X 0 0 0Packet tracing attack 0 0 X 0 X X X X X X X 0 0 0Brute-force attack X X X X X X X X X X X X X X X X indicates fully supported X indicates not supported 0 indicates partially supported

a distributed aggregate privacy-preserving authenticationprotocol called DAPPA which is robust and resilient to theSybil attacks in the IoV environment Using a token-basedauthentication approach Jan et al [143] proposed a payload-based mutual authentication protocol called PAWN in theIoS environment PAWNcan detect the Sybil attacks based onthe cluster formation between neighboring nodes and theirnearest cluster head

4 Countermeasures and Formal SecurityVerification Techniques

In order to satisfy the authentication model to secureIoT namely mutual authentication perfect forward secrecy

anonymity and untraceability the authentication protocolsuse both cryptosystems and non-cryptosystems countermea-sures Tables 11 12 13 and 14 present the cryptosystemsand countermeasures used in authentication protocols forM2M IoV IoE and IoS respectively In this section we willdiscuss the countermeasures and present the formal securityverification techniques used in these authentication protocolsfor the IoT

41 Countermeasures Based on the cryptosystems the exist-ing authentication protocols for the IoT can mainly be clas-sified into three categories symmetric-cryptosystem basedasymmetric-cryptosystem-based and hybrid protocols asshown in Figure 9 As presented in the following (Tables 11


Table 8 Approaches for detecting and avoiding the man-in-the-middle attack

Protocol Data attacked Approach

Lai et al (2016) [61] Communication channel between the mobilemanagement entity and the home subscriber server

Mutual authentication and key agreementbetween multiple M2M devices and thecore network simultaneously

Lai et al (2013) [38] The data between the mobiles equipmentrsquos and the3GPP network Authentication acknowledge phase

Cespedes et al (2013) [39] (i) Identify a shared key between two legitimate users(ii) Impersonate a mobile router or a relay router

The keys generated at the mobile routerand the relay router for authentication arebased on the concept of symmetricpolynomials

Dolev et al (2016) [66] Communication channel between the vehicles (i) Twofold authentication(ii) Periodic certificate restore

Nicanfar et al (2011) [139]

(i) Communication channel between the smart meterand the authentication agent(ii) Communication channel between theauthentication agent and the security associate (SA)server

All packets are fully encrypted with thereceivers public key

Nicanfar et al (2014) [142] The passwords of smart meter Changing the server password more oftenDas (2016) [72] The login request message during the login phase Password and biometric update phaseLai et al (2013) [37] Can occur while connecting to a base station Authentication acknowledge phaseFarash et al (2016) [75] Data between the sensor node users and gateway node Mutual authenticationJiang et al (2017) [77] Data between the Sensor node users and Gateway node Mutual authenticationWu et al (2016) [146] Data between the Sensor node users and Gateway node Mutual authenticationDas et al (2016) [147] The loststolen smart card of a legal user Password change phase

Attackerrsquos Network

False BTS

False MS

False MS

Legitimate MS

Legitimate BTS

Legitimate Network

Figure 4 MITM attack on GSM as defined by Conti et al in [13]BTS Base Transceiver Station MS Mobile Station

12 13 and 14) most authentication protocols use a securecryptographic hash function [149]

As presented in Table 11 the protocol [137] uses threecryptosystems namely original data acquisition spatial-domain transformation and time-domain transformationThe protocol [62] use two matching algorithms namelycorrelation coefficient-based matching algorithm (C-MA)and deviation ratio-based matching algorithm (D-MA) Theaggregate message authentication codes (AMACs) [150] areused by both schemes [37 61]TheAMAC tool is a tuple of thefollowing probabilistic polynomial time algorithms Authen-tication algorithm Aggregation algorithm and Verification

algorithm The authentication algorithm outputs a 119905119886119892 tagwhere the aggregate of tags can be simply computing the XORof all the tag values that is 119905119886119892 = 1199051198861198921oplus1199051198861198922oplussdot sdot sdotoplus119905119886119892119897 where1 119897 are identifiers The protocol [46] uses certificatelessaggregate signature [151] which enables an algorithm toaggregate 119899 signatures of 119899 distinctmessages from 119899 users intoa single short signature In addition the certificateless aggre-gate signature scheme is secure against existential forgery inthe chosen aggregate model The aggregate signature genera-tor computes 119881 = sum119899119894=1 119881119894 and outputs 120590119899 = (1198801 119880119899 119881)as an aggregate signature The protocol [38] uses EllipticCurve Diffie-Hellman (ECDH) [152] which is an anonymouskey agreement protocol The protocol [34] uses ID-basedsignature scheme [153] that consists of four algorithms SetupExtract Sign and Verify With Setup algorithm the trustauthority chooses efficiently computable monomorphismsThe trust authority performs the Extract algorithm when asigner requests the secret key corresponding to their identityThe 119878119894119892119899 algorithm produces a signature from the user withidentity 119868119863 on the message 119898 Therefore the protocol [53]uses advanced encryption standard (AES) [154] which is asymmetric encryption standard intended to replace the DataEncryption Standard (DES) [222] that has become too weakin view of current attacks The protocol [47] uses the LinearCombination Encryption (LCE) [155] which is an extensionof ElGamal encryption [223] that is secure in groups wherethe Decision Diffie-Hellman (DDH) problem is easy but theComputational Diffie-Hellman (CDH) problem is hardWiththe LCE scheme [155] a userrsquos public and secret keys aredefined as 119901119896 = (119906 V 1199081 = 119906119909 1199082 = V119910) and 119904119896 = (119909 119910)


Table 9 Approaches for detecting and avoiding the impersonation and forging attack


Wasef and Shen (2013) [40] Forge the revocation check (i) Linear search algorithm(ii) Binary search algorithm

Chung et al (2016) [69] Impersonate the mobile node Login and authentication phase

Das (2016) [72] Eavesdrop or intercept the login request message of theprevious sessions Authentication and key agreement phase

Wu et al (2016) [146] The data produced by the smart card in the Login phase Elliptic curve cryptosystem

Das et al (2016) [147] Eavesdrop modify or delete the contents of thetransmitted messages Password and biometric update

Sun et al (2015) [53] Information leakage of the M2M server The authentication process based onpassword

Lai et al (2014) [47] Forge andor modify the authentication messages

(i) Strong anonymous accessauthentication(ii) User tracking on a disputed accessrequest

Dolev et al (2016) [66] Forge andor modify the authentication messages Two rounds of session key

Kumari et al (2016) [68] Impersonation of user and sensor nodeGateway wireless node does not maintainany record to store user-specificinformation

Amin and Biswas (2016)[70] Intercepts the login request message Authentication and key agreement

Gope and Hwang (2016)[71] The serverrsquos secret key Adversary has no knowledge about the

secret identity of the gateway

Jiang et al (2016) [74] Gets the user smart cardThe hash mechanism using the sharedkey between gateway wireless node andsensor

Srinivas et al (2017) [144] Impersonation of the gateway node Noninvertible cryptographic one wayhash function property

Kumari et al (2016) [76] Impersonation of the gateway node Secret session keyJiang et al (2017) [77] Gets the user smart card PasswordLiu and Chung (2016) [148] Intercepts the login request message Password

False MS

－３1 －３2

－３3

I am －３1

I am－３

1

－３1 rsquos IP addr


(a) Before the impersonation attack

False MS

－３1 －３2

－３3

I am －３ 1

I am －３1

－３1rsquos IP addr

－３ 1rsquos

IP addr

(b) After the impersonation attack

Figure 5 Impersonation attack MS Mobile Station

where 119906 Vlarr 1198661 and119909 119910 larr 119885lowast119901Themessage119872 is encryptedto (1198631 = 119906

119886 1198632 = V119887 1198633 = 119872 sdot 11990811988611199081198872) where 119886 119887 isin 119885

lowast119901 are

randomThen the original message119872 is decrypted from theciphertext (1198631 1198632 1198633) by1198633 sdot (119863

1199091 sdot 1198631199102 )minus1

As presented in Table 12 the protocol [39] uses bothcountermeasures namely Proxy Mobile IP (PMIP) [156]

and Symmetric Polynomials [157] The PMIP is a localizednetwork based IP mobility protocol (RFC 5213 [224]) thatdefines two entities the Mobile Access Gateway (MAG)and the Local Mobility Anchor (LMA) The symmetricpolynomial is defined as any polynomial of two or morevariables that achieves the interchangeability property thatis119891(119909 119910) = 119891(119910 119909) For example given two users identities 1


Table 10 Approaches for detecting and avoiding the replay attack


Lai et al (2013) [38] Replaying the data between the mobiles equipment and the 3GPPnetwork Random numbers

Sun et al (2015) [53] Replaying the intercepted login message Random numbers

Lai et al (2013) [37] Replaying the message between serving gateway and home subscriberserver Random numbers

Cespedes et al (2013) [39] Replaying one of the router solicitation messages Random numbersWasef and Shen (2013) [40] Replaying the disseminated messages in IoV TimestampShao et al (2016) [63] Replaying the disseminated messages in IoV TimestampZhang et al (2016) [52] Replaying the disseminated messages in IoV TimestampLi et al (2014) [49] Replaying the electricity consumption reports Merkle hash tree techniqueNicanfar et al (2011) [139] Replaying the electricity consumption reports TimestampChim et al (2011) [140] Replaying the electricity consumption reports TimestampFouda et al (2011) [141] Replaying the electricity consumption reports Timestamp

Nicanfar et al (2014) [142] Forwarding a previous acknowledgment from the smart meter to theserver Timestamp

Mahmood et al (2016) [67] Intercept messages by home area network and replay those archaicmessages to building area network gateway Timestamp

Kumari et al (2016) [68] Intercept and replay the login request to gateway wireless node Timestamp

Jan et al (2016) [143] Eavesdrop on advertisement packets andor join-request packets andreplay in other parts of the network Hash function and ring keys

Amin and Biswas (2016) [70] Replaying the message in the IoS TimestampDas (2016) [72] Replaying the login request message TimestampChang and Le (2016) [73] Replaying the login request message TimestampFarash et al (2016) [75] Replaying the login request message TimestampSrinivas et al (2017) [144] Replaying the messages in the IoS TimestampKumari et al (2016) [76] Intercept and replay the login request to gateway wireless node TimestampJiang et al (2017) [77] Intercept the login request TimestampLiu and Chung [148] Intercept the login request Timestamp

False MS

Legitimate MSLegitimate MSD1 D2 D3

D3

Figure 6 Replay attack MS Mobile Station

and 2 and the symmetric polynomial119891(119909 119910) = 11990921199102+119909119910+10the resultant evaluation functions are119891(1 119910) = 1199102+119910+10 and119891(2 119910) = 41199102 + 2119910 + 10 respectively Then if user 1 evaluatesits function 119891(1 119910) for user 2 it obtains 119891(1 2) = 16 In thesame way 119891(2 119910) for user 1 user 2 obtains 119891(1 2) = 16 As aresult both users share a secret key 16 without transmitting

False MSMS

Normal linkWormhole tunnel

Figure 7 Wormhole attack

any additional messages to each other Contrary to this ideaof symmetric polynomials the protocol [40] uses the idea ofsearch algorithms [158] which include nonoptimized searchalgorithms such as linear search algorithm and optimizedsearch algorithms such as binary search algorithm andlookup hash tables In another work [159] Chaum and vanHeyst introduce the idea of group signatures in order to


False MS

False MS

Attackerrsquos NetworkLegitimate Network

False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges

Figure 8 Sybil attack MS Mobile Station

provide anonymity for signers The protocol [63] uses thisidea based on the Strong Diffie-Hellman assumption andthe Decision Linear assumption The protocol [64] usesthree countermeasures namely (1)Merkle Hash Tree (MHT)[161] (2) TESLA scheme [162] and (3) Elliptic Curve DigitalSignature Algorithm (ECDSA) [163] The MHT is a binarytree structure where each leaf is assigned a hash value andan inner node is assigned the hash value of its children Toachieve source authentication the TESLA scheme uses one-way hash chains with the delayed disclosure of keys basedon symmetric cryptography The protocol [65] uses multi-plicative secret sharing technique [164] where the user cangenerate one-time pseudonym private key pairs and leakage-resilient locally Similar to the protocol [63] the protocol [66]uses the idea of digital signatures [167]The protocol [48] useskeyed-hashing for message authentication (HMAC) [169]to instantiate the pseudorandom function in the prototypeimplementation of electric vehicle ecosystem The protocol[52] uses two similar ideas namely identity-based public keycryptosystem [165] and identity-based aggregate signature[166] For providing a flexible attribute management theprotocol [54] uses an anonymous attribute-based group setupscheme [168] that incorporates the policy-based data accesscontrol in the ciphertext

As presented in Table 13 the protocol [28] uses twotypes of verification namely Heavy signing light verifica-tion (HSLV) and Light signing heavy verification (LSHV)which is based on the HORS scheme [170] The HSLVuses the following three algorithms Key Generation Signingand Verification The Key Generation algorithm outputs thepublic key 119875119870 = (119896 V1 V2 V119905) and the secret key119878119870 = (119896 1199041 1199042 119904119905) where the trusted authority gen-erates 119905 random 119897-bit strings 1199041 1199042 119904119905 The signature is(119888 (1199041198941 1199041198942 119904119896)) generated by the Signing algorithm Toverify a signature (1198881015840 (11990410158401198941 119904

10158401198942 119904

1015840119896)) over message 119898 the

user check if the output integers 1198941 gt 1198942 gt 119894119896 and

119891(1199041015840119895) = V119894119895 holdOn the other handwith LSHV the signatureverification process verifies the 119896 elements of a signature byapplying the one-way function for a distinct number of timesover each element Similar to the protocol [64] the protocol[49] uses the same idea of Merkle Hash tree technique [171]In order to increase the level of security the protocol [138]uses three cryptosystems namely short signatures (BLS)[172] batch verification [173] and signature aggregation[174] The BLS is introduced by Boneh-Lynn-Shacham [172]which is based on Gap Diffie-Hellman groups Specificallythe BLS scheme uses the following three algorithms (1) Keygeneration algorithm to output the public key V isin 1198662 andthe private key 119909 where 119909 larr 119885119901 and V larr 1198922

119909 (2) Signingalgorithm to generate a signature 120590 isin 1198661 where 120590 larr ℎ119909 andℎ larr 119867(119872) isin 1198661 and (3)Verification algorithm to verify that(1198922 V ℎ 120590) is a valid co-Diffie-Hellman tuple The author ofshort signatures (BLS) [172] that is Boneh et al proposesthe idea of signature aggregation [174] where an aggregatesignature is valid only if it is an aggregation of signatures ondistinct messages Similar to the protocol [39] the protocol[139] uses the same cryptosystem that is identity-basedpublic key cryptosystem [165] Therefore both protocols [55140] use the two same cryptosystems namely (1) the publickey encryption such as RSA [175] and (2) HMAC such asSHA-1 [176] andMD5 [177]Theprotocol [141] uses theDiffie-Hellman key establishment protocol [178] in order to provideforward secrecy in Transport Layer Securityrsquos ephemeralmodes The protocol [142] uses the EIBC mechanism [179]which is based on the originalmodel developed by Boneh andFranklin In addition the protocol [55] uses the Homomor-phic Encryption [181] and theBloomFilter [182]Theprotocol[67] uses two cryptosystems (1) HMAC such as SHA-1 [176]and MD5 [177] and (2) a symmetric encryptiondecryptionalgorithm [178] As presented in Table 14 the protocol [68]uses two countermeasures namely Chebyshev ChaoticMaps[183] and Semigroup Property of Chebyshev Polynomials


Table 11 Cryptosystems and Countermeasures used in authentication protocols for Machine to Machine Communications (M2M)

Cryptosystems and countermeasures Authentication protocols for M2M[62] [61] [46] [38] [34] [53] [47] [137] [37]

Secure cryptographic hash function [149]

Original data acquisition

Spatial-Domain transformation

Time-domain transformation

Correlation coefficient-based matching algorithm (C-MA)

Deviation ratio-based matching algorithm (D-MA)

Aggregate message authentication codes (AMACs) [150]

Certificateless aggregate signature [151]

Elliptic Curve Diffie-Hellman (ECDH) [152]

ID-based signature scheme [153]

Advanced encryption standard (AES) [154]

Hybrid Linear Combination Encryption [155]

Table 12 Cryptosystems and countermeasures used in Authentication protocols for Internet of Vehicles (IoV)

Cryptosystems and countermeasures Authentication protocols for IoV[39] [40] [63] [64] [65] [66] [48] [52] [54]


Proxy Mobile IP (PMIP) [156]

Symmetric polynomials [157]

Search algorithms [158]

Group signature [159 160]

Merkle hash tree (MHT) [161]

TESLA scheme [162]

ECDSA signature [163]

Multiplicative secret sharing technique [164]

Identity-based public key cryptosystem [165]

Identity-based aggregate signature [166]

Digital signatures [167]

Anonymous attribute-based group setup scheme [168]

Keyed-hashing for message authentication (HMAC) [169]

Table 13 Cryptosystems and countermeasures used in authentication protocols for Internet of Energy (IoE)

Cryptosystems and countermeasures Authentication protocols for IoE[28] [49] [138] [139] [140] [141] [142] [55] [67]


HORS scheme [170]

Heavy signing light verification (HSLV) [170]

Light signing heavy verification (LSHV) [170]

Merkle Hash tree technique [171]

Short signatures (BLS) [172]

Batch verification [173]

Signature aggregation [174]


Public-key encryption such as RSA [175]

HMAC such as SHA-1 [176] and MD5 [177]

Diffie-Hellman key establishment protocol [178]

EIBC mechanism [179]

ID-based cryptography (IBC) [180]


Homomorphic encryption [181]

Bloom filter [182]

Commitment scheme

Symmetric encryptiondecryption algorithm [178]


Table 14 Cryptosystems and countermeasures used in authentication protocols for Internet of Sensors (IoS)

Cryptosystems and countermeasures Authentication protocols for IoS[68] [69] [143] [70] [71] [72] [73] [74] [75] [144] [76] [145] [77] [146]


Chebyshev chaotic maps [183]

Chebyshev polynomials [184]



Biometric

Password

Smart card

Fuzzy extractor technique [186]


Key agreement

Biohashing [187]

Access polynomial [188]

Elliptic curve cryptography [189]

Authentication protocols for the IoT

M2M IoV IoE IoS

Symmetric-cryptosystem- cryptosystem-based protocols based protocols

Authentication protocols that use Authentication protocols that useAuthentication protocols that use

TwoshSerpent AES (Rijndael) Blowsh CAST5 Kuznyechik RC4 3DES Skipjack

Asymmetric-

Die-Hellman key exchange protocol DSS (Digital Signature Standard)ElGamal agreement techniquesPaillier cryptosystemRSA encryption algorithm (PKCS1)CramerndashShoup cryptosystemYAK authenticated key agreement protocol

Hybrid protocols

BiometricPasswordSmart cardFuzzy extractor techniqueBiohashingAccess polynomialSecure cryptographic hash function

Various elliptic curve techniquesVarious password-authenticated key

and so on

and so on

and so on

Figure 9 Classification of the existing authentication protocols for the IoT based on the cryptosystems

[184] The Chebyshev Polynomial of degree 119901 is defined byMason and Handscomb [183] as 119879119901(119909) = cos(119901119883 acrcos119909)where the domain is the interval 119909 isin [minus1 1] with twoproperties [225] However three protocols that is [69ndash71]use the ID-based cryptography (IBC) [180] On the otherhand the protocol [143] uses the Advanced EncryptionStandard (AES) [185] such as the protocol [53] The smartcard-based authentication protocols are a very promisingand practical solution to remote authentication [226] aspresented in Table 15 There are five [72ndash75 144] smartcard-based authentication protocols where each protocolintegrates a method with the smart card For example theprotocol [72] uses the fuzzy extractor technique [186] where

a fuzzy extractor is a pair of randomized procedures ldquogener-aterdquo (Gen) and ldquoreproducerdquo (Rep) and is efficient if Gen andRep run in expected polynomial time For more details aboutthe fuzzy extractor technique we refer the reader to the paper[186] In addition the elliptic curve cryptography [189] is usedby both protocols [77 146]

42 Formal Security Verification Techniques In order toprove the performance of an authentication protocol interms of security researchers use formal security verifica-tion techniques As presented in Figure 10 there are fiveformal security verification techniques namely BAN-logicanalysis by process (Spi calculus) Game Theory Automated


Table 15 The smart card-based authentication protocols

Protocol Type Design goal

Das (2016) [72] Remote authentication Providing a user authentication to resolve the securityweaknesses of the scheme [190]

Chang and Le (2016) [73] Remote authentication Providing mutual authentication and perfect forward secrecyJiang et al (2016) [74] Remote authentication Providing mutual authentication anonymity and untraceability

Farash et al (2016) [75] Remote authentication Providing the user authentication with traceability protectionand sensor node anonymity

Srinivas et al (2017) [144] Remote authentication Providing the mutual authentication with anonymity andunlinkability

BAN-logic

Analysis byprocess(Spi calculus)

Gameeory

Formal securityverification technique

Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

Figure 10 Formal security verification techniques used by thesurveyed protocols

reasoning (ProVerif) and Automated Validation (AVISPA)In addition Table 16 presents the formal security verificationtechniques used in authentication protocols for the IoT

The Burrows-Abadi-Needham Logic (BAN-logic) [195] isused by nine authentication protocols [68ndash70 74ndash77 144147] A typical BAN-logic sequence includes three steps (1)verification of message origin (2) verification of messagefreshness and (3) verification of the originrsquos trustworthinessTherefore the protocol [68] uses the BAN-logic to prove thatthe proposed protocol can establish a session key betweenuser and sensor node Both protocols [69 77] use the BAN-logic in order to prove that the protocol has achieved mutualauthentication and session key agreement securely The pro-tocol [144] uses the BAN-logic to prove that the protocol canresist numerous security attacks which include the attacksfound in the Amin and Biswasrsquos scheme [70] There areseven authentication protocols [70 72 75 142 144 147197] that use the Automated Validation of Internet SecurityProtocols and Application (AVISPA) security analyzer [194]The AVISPA tool provides a modular and expressive formallanguage for specifying security protocols and propertiesThe protocol [197] uses the AVISPA tool in order to prove

that the proposed protocol is free from man-in-the-middleand replay attacks The protocol [75] uses the AVISPA toolto prove that the protocol allows a user to establish asession key with a sensor node of his choice near the endof the authentication process In addition there are fourauthentication protocols [37 38 67 146] that use the ProVeriftool [191] which is an automatic cryptographic protocolverifier in the formal model called Dolev-Yao model [196]The protocol [38] uses the ProVerif tool in order to proof themutual authentication between the mobile equipment andits serving network The protocol [37] uses the ProVerif toolto prove that the proposed protocol can implement mutualauthentication and key agreement between multiple devicesand the core network simultaneouslyThe protocol [146] usesthe ProVerif tool to prove that the proposed protocol canpass the verifications according to theDolev-Yaomodel [196]Finally the protocol [73] uses a sequence of games underthe decisional Diffie-Hellman (ECDDH) problem in order toproof that the protocol provides secure and perfect forwardsecrecy authentication For more details about the game-theoretic approaches we refer the reader to the survey [227]

5 Taxonomy and Comparison ofAuthentication Protocols for the IoT

In this section we examine in detail authentication proto-cols developed for or applied in the context of IoT As shownin Figure 11 the realization processes of an authenticationprotocol for IoT are based on the following processes

(1) Definition of network model (eg M2M IoV IoEand IoS)

(2) Definition of authentication model (eg mutualauthentication perfect forward secrecy anonymityand untraceability)

(3) Definition of attacks model (eg replay attack stolensmart card attack privileged-insider attack offlinepassword guessing attack impersonation attack andsensor node capture attack)

(4) Selection of countermeasures (eg cryptographicmethods Bloom Filter biometric Smart card accesspolynomial and Chebyshev Chaotic Maps)

(5) Proposition of main phases of the protocol (eginitial setup registration process)


Table 16 Formal security verification techniques used in authentication protocols for the IoT

Protocol Approach Main results

Lai et al (2013) [38] The security of the protocol is analyzedusing the ProVerif tool [191]

Proof the mutual authentication between mobileequipment and its serving network

Shao et al (2016) [63]

(i) Decisional Diffie-Hellman (DDH)Assumption(ii) Decision Linear (DLIN) Assumption(iii) Extended ComputationalDiffie-Hellman (eCDH) Assumption(iv) Computational InverseDiffie-Hellman (ciCDH) Assumption

(i) The proposed group signature scheme satisfiesunforgeability(ii) The proposed group signature scheme satisfiesanonymity(iii) The proposed theorem satisfies the traceability

Zhang et al (2016) [65] Based on the size of the beacon intervaland the network bandwidth

Broadcasting the MAC of a messagersquos prediction outcomeis secure

Zhang et al (2016) [52]Bilinear Diffie-Hellman and thecomputational Diffie- Hellmanassumptions

The protocol satisfies individual authenticationnon-repudiation vehicle privacy and traceability

Dolev et al (2016) [66] Spi calculus [192] The proposed session key establishment protocol respectsthe authenticity property and the secrecy property

Chan and Zhou (2014)[48] NXP-ATOP platform [193] Demonstrate the two-factor cyber-physical device

authentication


The scheme can implement mutual authentication and keyagreement between multiple devices and the core networksimultaneously

Li and Cao (2011) [28] Prove the existence of a pivot rank bycontradiction The total signing cost does not increase

Li et al (2012) [138] Diagnose tools Detect failure points and to minimize the whole fault time

Nicanfar et al (2014)[142]

Automated Validation of InternetSecurity Protocols and Application(AVISPA) security analyzer [194]

Providing mutual authentication and key managementmechanisms

Mahmood et al (2016)[67]

The security of the protocol is analyzedusing the ProVerif tool [191]

Verifies mutual authentication and session key secrecyproperties of the proposed scheme

Kumari et al (2016) [68] Burrows-Abadi-Needham Logic(BAN-logic) [195]

Prove that the proposed scheme establishes a session keybetween user and sensor node

Chung et al (2016) [69] Burrows-Abadi-Needham Logic(BAN-logic) [195]

Prove the validity of authentication and key agreementprotocol

Amin and Biswas (2016)[70]

(i) Burrows-Abadi-Needham Logic(BAN-logic) [195](ii) Automated Validation of InternetSecurity Protocols and Application(AVISPA) security analyzer [194]

Prove that the protocol has achieved mutualauthentication and session key agreement securely

Das (2016) [72]Automated Validation of InternetSecurity Protocols and Application(AVISPA) security analyzer [194]

The scheme is secure against the replay andman-in-the-middle attacks against an adversary

Chang and Le (2016) [73] Sequence of games under the decisionalDiffie-Hellman (ECDDH) problem

The scheme provides secure and perfect forward secrecyauthentication

Jiang et al (2016) [74] Burrows-Abadi-Needham Logic(BAN-logic) [195]

The improved scheme accomplishes mutual authenticationand key agreement between the user and sensor the userand the gateway node

Farash et al (2016) [75]


Prove that the scheme allows a user to establish a sessionkey with a sensor node of his choice near the end of theauthentication process

Srinivas et al (2017)[144]


The scheme can resist numerous security attacks whichinclude the attacks found in Amin and Biswasrsquos scheme[70]


Table 16 Continued



The scheme provides secure mutual authenticationbetween a legal user and an accessed sensor node insideWSN or not


Prove that an identity and a session key is agreedbetween the user and the sensor

Wu et al (2016) [146] The security of the protocol is analyzedusing the ProVerif tool [191]

The scheme passes the verifications according to theDolev-Yao model [196]

Das et al (2016) [147]

(i) Burrows-Abadi-Needham Logic(BAN-logic) [195](ii) Random oracle model(iii) Automated Validation of InternetSecurity Protocols and Application(AVISPA) security analyzer [194]

Prove secure mutual authentication between a legaluser and an accessed sensor node

Das et al (2016) [197]Automated Validation of InternetSecurity Protocols and Application(AVISPA) security analyzer [194]

The scheme is free from man-in-the-middle and replayattacks

(i) Machine to MachineCommunications (M2M)

(ii) Internet of Vehicles (IoV)(iii) Internet of Energy (IoE)(iv) Internet of Sensors (IoS)

Denition ofDenition of authentication

model

(i) Mutualauthentication

(ii) Perfect forwardsecrecy

(iii) Anonymity

Denition ofattacks model

(i) Replay attackstolen smart cardattack

(ii) Privileged-insiderattack

(iii) Oine passwordguessing attack

(iv) Impersonationattack

(v) Sensor nodecapture

Selection ofcountermeasures

(i) Cryptographicmethods

(ii) Bloom Filter(iii) Biometric(iv) Smart card(v) Fuzzy extractor

technique(vi) Access polynomial(vii) Chebyshev Chaotic

Maps

Proposition ofmain phasesof the protocol

(i) Initialization(ii) Authentication(iii) Message

transmission

Securityanalyses usingformalsecurityverication(i) ProVerif(ii) BAN-logic(iii) AVISPA(iv) Resistance to

attacks

Performanceevaluation

(i) Communicationoverhead

(ii) Storage cost(iii) Computation

complexity(iv) Lower error rates

network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability

Figure 11 The realization processes of an authentication protocol for the IoT

(6) Security analyses using formal security verification(eg ProVerif BAN-logic and AVISPA)

(7) Performance evaluation (eg in terms of storage costcomputation complexity communication overheadand lower error rates)

Figure 12 presents the categorization of authenticationmodels for the IoT We note that some of the papers may beclassified into multiple authentication models We circum-vented this ambiguity by classifying the papers accordingto the IoT environment as presented in Figure 13 that is(1) authentication protocols for M2M (2) authenticationprotocols for IoV (3) authentication protocols for IoE and(4) authentication protocols for IoS

51 Authentication Protocols for M2M The surveyed papersof authentication protocols for Machine to Machine com-munications (M2M) as shown in Table 17 are publishedbetween 2012 and 2016 In order to speed up the process ofauthentication and avoid authentication signaling overloadLai et al [61] focused on the problem of group authenti-cation and key agreement for resource-constrained M2Mdevices in 3GPP networks Specifically the authors proposed

a novel group-based lightweight authentication scheme forresource constrained M2M called GLARM The networkmodel used in [61] is based on 3GPP standard with threedomains including access networks evolved packet core andnon-3GPP domain for example Internet To guarantee theentity mutual authentication and secure key agreement theGLARM scheme uses twomain phases namely (1) Initializa-tion phase and (2) Group authentication and key agreementphase In addition the GLARM scheme can ensure QoS formachine-type communications devices but the computationcomplexity is much less than schemes [32 38 46] In orderto distinguish between different physical devices running thesame software and detecting mimic attacks Chen et al [62]proposed an authentication protocol for the IoT named S2MThe S2M protocol uses tree main phases namely (1) audio-handshake phase (2) mixed-signal generation phase and(3) feature extraction and storage phase S2M can achievevariable distance authentication and active attack detectionusing acoustic hardware (SpeakerMicrophone) fingerprintsIn addition S2M is efficient in terms of lower error ratescompared with DISWN [198] LDTLS [199] PLTEA [200]and SeArray [201] but the performance of the methods in


Table 17 Summary of authentication protocols for M2M

Prot Network model Goals Main processes Performances (+) and limitations(minus)

Lai et al(2016) [61]

Based on 3GPP standard withthree domains includingaccess networks evolvedpacket core and non-3GPPdomain eg Internet

Guarantee the entitymutual authentication andsecure key agreement

(i) Initialization phase(ii) Group authenticationand key agreement phase

+ Resistance to DoS attackredirection attack andman-in-the-middle attack+ Computation overheads arefairly small+ Computation complexity ismuch less than schemes[32 38 46]+ Can ensure QoS formachine-type communicationsdevicesminus Some privacy models are notanalyzed such as location privacyand identity privacyminus Storage costs is not considered

Chen et al(2017) [62] Two wireless devices

Achieving variable distanceauthentication and activeattack detection

(i) Audio-handshake phase(ii) Mixed-signalgeneration phase(iii) Feature extraction andstorage phase

+ Efficient in terms of lower errorrates compared with DISWN[198] LDTLS [199] PLTEA[200] and SeArray [201]+ Active attack detection (egaudio replay attack)minus Privacy-preserving is notanalyzed compared to theGLARM scheme [61]minus Storage costs is not considered

Lai et al(2014) [46]

3GPP-WiMAX-Machine-typeCommunication

Achieving mutualauthentication and keyagreement between allMachine-typeCommunication devices

(i) Initialization phase(ii) Roaming phase

+ Efficient in terms of thecommunication overheadcompared to the traditionalroaming authentication schemeand the optimized roamingauthentication scheme in [34]+ Efficient in terms ofcomputation complexitycompared to the scheme withoutaggregationminus Resistance to attacks is notstudiedminus Privacy-preserving is notanalyzed compared to theGLARM scheme [61]minus Storage costs is not considered

Lai et al(2013) [38]

3GPP standard with threedomains namely accessnetwork domain servingnetwork domain and homenetwork domain

Guaranteeprivacy-preservation andkey forwardbackwardsecrecy with

(i) Preparation andinitialization(ii) Protocol execution forthe first equipment(iii) Protocol execution forthe remaining equipmentof the same group(iv) Group memberjoiningleaving the group

+ Considers the data integrityand ensure user privacy+ Resistance to attacks (DoSattack redirection attackman-in-the-middle attack andreplay attack)+The overhead of authenticationmessage delivery of SE-AKA islower than other existing AKAprotocols+The computational overhead islarger than that of othertraditional protocols such as thework [202]+ Smaller storage costs thanothers protocolsminus Some privacy models are notanalyzed such as location privacyand identity privacy


Table 17 Continued


Fu et al(2012) [34]

Mobile WiMAX networkswith an access service network

Achieving mutualauthentication and privacypreservation and resistingthe domino effect

(i) Predeployment phase(ii) Initial authenticationphase(iii) Handoverauthentication phase

+ Efficient in terms of thecomputational andcommunication overheadcompared to three schemes[39 203 204]+ Considers the privacypreservationminus Storage costs is not consideredminus Resistance to attacks is notstudiedminus No threat model presentedminus Error-detection and faulttolerance are not considered

Sun et al(2015) [53]

Mobile users home gatewaysand an M2M server

Achieving a mutualauthentication process inmachine-to machine homenetwork service

(i) Set-up(ii) Registration phase(iii) Login andauthentication phase(iv) Update password phase(v) Home gateway joins theTimeDivision-SynchronousCode Division MultipleAccess network

+ Efficient in terms of theamount of calculation andcommunication volumecompared to the protocol in[205]+ Resistance to guessing attackstolen-verifier attackimpersonation attack and replayattackminus Privacy-preserving is notanalyzed compared to theGLARM scheme [61]minus Storage costs is not consideredminus Lack nonrepudiationcompared to the PBA scheme in[64]

Lai et al(2014) [47]

Roaming network architecturewith the home authenticationcenter (HAC) the trustlinking server (TLS) and thevisiting authentication server(VAS)

(i) Providing a stronganonymous accessauthentication(ii) Guarantee user trackingon a disputed access request(iii) Achieving anonymoususer linking and efficientuser revocation fordynamic membership

(i) System initialization(ii) Roaming(iii) User trackingalgorithm(iv) Anonymous userlinking(v) User revocation

+ Efficient in terms ofcommunication overhead andcomputation cost compared totwo strong anonymous schemes[17 26]+ Considers the data integrityand ensure user privacy+ Resistance to attacks namelyDenial of Service (DoS) attackand impersonation attackminus Some privacy models are notanalyzed such as location privacyminus Lack nonrepudiationcompared to the PBA scheme in[64]

Zhu et al(2015) [137] Android smartphone devices

(i) Satisfy theuser-friendliness with areasonable false rejectionrate(ii) Achieving anauthentication process forAndroid smartphonedevices

(i) Feature-set extractionand storing for registration(ii) Dual-factorauthentication

+ Can enhance user-friendliness+ Improve security withoutadding extra hardware devicesminus No threat model presented


Fast reauthenticationAuthenticationandKey Agreement

Deniable authenticationCross-realm

authentication

Mutual authentication

Authenticationmodels for theIoT

RFID authentication

Handoverauthentication Group-based

handoverauthentication

Password-basedauthentication

Biometricauthentication

Fingercodeauthentication

Identity basedauthentication

ree-factorauthentication

Remote userauthentication

Smart-card-basedauthentication

Figure 12 Categorization of authentication models for the IoT

Authentication protocols forIoS

Authentication protocols forIoV

Authentication protocolsfor the IoT

Authentication protocols forIoE

Authentication protocols forM2M

Figure 13 Classification of authentication protocols for the IoT based on the IoT environment

terms of privacy preservation is not analyzed especially incomparison to the GLARM scheme [61]

To authenticate a group of devices at the same time Laiet al [46] proposed a scheme named SEGR Based on roam-ing phase SEGR can achieving mutual authentication andkey agreement between all Machine-type Communication(MTC) devices when a group ofMTC devices roams between3GPP and WiMAX networks SEGR is efficient in termsof the communication overhead computation complexitycompared to the scheme in [34] and the scheme withoutaggregation but again a comparisonwith othermethods suchas the GLARM scheme [61] regarding privacy preservation ismissing We also note that resistance to attacks of the SEGRmethod is not studied in the article as well [46] To guaranteeprivacy preservation and key forwardbackward secrecy Laiet al [38] proposed an efficient group authentication andkey agreement protocol called SE-AKA which is based onauthentication and key agreement (AKA) protocolThe over-head of authentication message delivery of SE-AKA is lowerthan other existing AKA protocols but the computationaloverhead is larger than that of other traditional protocolssuch as the work [202] In addition SE-AKA has smallerstorage costs than others AKA protocols Similar to the SE-AKA protocol Lai et al in [37] proposed a lightweight groupauthentication protocol for M2M called LGTH which isefficient in terms of the signaling and computation overheadcompared to the schemes [32 228] Similar to the SE-AKA amp LGTH protocols Fu et al [34] proposed a group-based handover authentication scheme for mobile WiMAX

networks Based on the handover authentication phase thework [34] is efficient in terms of the computational andcommunication overhead compared to three schemes [202ndash204] but the resistance to attacks is not studied and no threatmodel is presented

In order to achieve a mutual authentication process inmachine to machine home network service Sun et al [53]proposed anM2M applicationmodel for remote access to theintelligence home network service using the existing TimeDivision-Synchronous Code Division Multiple Access (TD-SCDMA) systemThe protocol [53] is efficient in terms of theamount of calculations needed and communication volumecompared to the protocol in [205] but the article lacksa comparison of performance in terms of nonrepudiationagainst other schemes such as the PBA [64] To achieve theauthentication of mobile subscribers in the roaming serviceLai et al [47] proposed a conditional privacy-preservingauthenticationwith access linkability calledCPALTheCPALcan (1) provide a strong anonymous access authentication(2) guarantee user tracking on a disputed access requestand (3) achieve anonymous user linking and efficient userrevocation for dynamic membership The CPAL is efficientin terms of communication overhead and computation costcompared to two strong anonymous schemes [17 26] butprivacy aspects are not analyzed such as location privacyWithout adding any extra hardware devices Zhu et al [137]proposed a dual-factor authentication scheme called Duthdesigned for Android smartphone devices Based on twomain processes namely (1) feature-set extraction and storing


for registration and (2) dual-factor authentication the Duthscheme can satisfy the user-friendly requirements alongwitha reasonable false rejection rate providing on the same timean authentication process for Android smartphone devices

Esfahani et al [229] proposed a lightweight authentica-tion scheme to ensure secure integration of Industrial Inter-net of Things (IIoT) solutions Specifically the work [229]considers an IIoT scenario where a machine equipped witha Secure Element (SE) is authenticated by a network elementequipped with a Trusted Platform Module (TPM) Basedon two procedures namely (a) the registration procedureand (b) the authentication procedure the work [229] ischaracterized by low computational cost communicationand storage overhead However based on the RF fingerprintof MTC devicesrsquo hardware Zhao et al [230] introduced theMTC architecture as well as a cross-layer authenticationscheme The work [230] can facilitate the interoperationof heterogeneous MTC networks In addition Qiu andMa [231] proposed an enhanced mutual authentication andkey establishment scheme for the M2M communications in6LoWPAN networks Compared to the protocol [230] thework [231] is analyzed by the Protocol Composition Logic(PCL)

Amin et al [232] proposed an architecture which isapplicable for a distributed cloud environment using smartcard Using AVISPA tool and BAN-logic model the protocol[232] is protected against user impersonation attack replayattack and session key discloser attack Recently Islam et al[233] proposed a three-factor session initiation protocol (SIP)formultimedia big fata communicationsThrough the formalverification using the BAN-logic the protocol is proved thatcan provide user anonymity and untraceability To protectthe confidential information in the device Amin et al[234] proposed a mutual authentication and key negotiationprotocol Based on the elliptic curve cryptography (ECC) theprotocol [234] provides the mutual authentication propertybetween the participants involved and provides a passwordupdate facility to registered users

52 Authentication Protocols for IoV The surveyed papersof authentication protocols for Internet of Vehicles (IoV)as shown in Table 18 are published between 2013 and 2016Cespedes et al in [39] considered the security associationbetween asymmetric links during Vehicle to Vehicle (V2V)communications More precisely the authors proposed amultihop authenticated proxy mobile IP scheme called MA-PMIP Based on authentication phase and mobile routerrevocation MA-PMIP can achieve less location update costcompared with the scheme [206] and the handover delaylower than the scheme [206] In addition MA-PMIP canachieve mutual authentication against authentication attacksbut the privacy-preserving is not analyzed compared tothe GLARM scheme [61] In order to expedite messageauthentication in VANET Wasef and Shen [40] proposedan expedite message authentication protocol named EMAPBased on the revocation checking process EMAP can over-come the problem of the long delay incurred in checking therevocation status of a certificate using a certificate revocationlist EMAP is efficient in terms of computational complexity

of revocation status checking and the authentication delayis constant and independent of the number of revokedcertificates Therefore the question we ask here is can theseprotocols work well in the decentralized group model Theauthentication scheme proposed recently by Shao et al in[63] can answer this question where it can achieve tworequirements for threshold authentication namely distin-guishability and efficient traceability The protocol in [63]is proven that is secured by three theorems namely (1) theproposed group signature scheme satisfies unforgeability (2)the proposed group signature scheme satisfies anonymityand (3) the proposed theorem satisfies the traceability

To achieve the nonrepudiation in IoV Lyu et al in [64]proposed a lightweight authentication scheme called PBABased on the idea of Merkle hash tree construction and self-generated MAC storage the PBA scheme can resist packetlosses and maintain high packet processing rate with lowstorage overhead The PBA is efficient in terms of overalldelay compared to the TESLA scheme in [162] and the VASTscheme in [161] Zhang et al in [52] considers a VANETwith four main entities that is key generator center (KGC)traffic management authority (TMA) RSUs and vehiclesBased on identity-based aggregate signatures the protocolin [52] can guarantee some properties such as messageauthentication nonrepudiation message confidentiality pri-vacy and traceability Similar to the scheme [52] Zhang etal [65] proposed an efficient distributed aggregate privacy-preserving authentication protocol called DAPPA which isbased on a new security tool called multiple-TA OTIBAS(MTA-OTIBAS) The DAPPA protocol can guarantee theconditional unlinkability ideal tamper-proof device (TPD)freeness and key escrow freeness In addition the DAPPAprotocol is efficient compared to the ECDSA protocol in[163] and more efficient than the IBA scheme in [52] onaverage but lacks nonrepudiation compared to the PBAscheme in [64] Based on monolithically certified publickey and attributes Dolev et al [66] proposed an idea toensure the countermeasures against the man-in-the-middleattack under the vehicle authentication The work in [66] isefficient in terms of iteration cost compared to other existingAuthenticated Key Exchange (AKE) protocols such as ISO-KE [207] and SIGMA [208] To defend against coordinatedcyber-physical attacks Chan and Zhou [48] proposed a two-factor cyber-physical device authentication protocol whichcan be applied in the IoV Especially in the IoT the vehiclesmay join or leave the platoon at any time in the platoon-basedvehicular cyber-physical system To guarantee anonymity ofplatoon members Lai et al [54] proposed a secure groupsetup and anonymous authentication scheme named SGSAfor platoon-based vehicular cyber-physical systems Basedon the anonymous authentication with traceability phasethe SGSA scheme can provide strong anonymous accessauthentication

Ferrag andAhmim [235] proposed a recent scheme basedon searchable encryption with vehicle proxy reencryptioncalled ESSPR for achieving privacy preservation of messagein the IoV environment ESSPR is robust against eavesdrop-ping attack wormhole attack packet analysis attack packettracing attack and replay attack


Table 18 Summary of authentication protocols for IoV


Cespedes et al(2013) [39]

A vehicularcommunications networkwith Access Routers (ARs)that connect the VANET toexternal IP networks

Achieving mutualauthentication againstauthentication attacks

(i) Key establishmentphase(ii) MR registrationphase(iii) Authenticationphase(iv) Mobile routerrevocation

+ Considers the asymmetriclinks in the VANET+ Achieving less location updatecost compared with the scheme[206]+The handover delay lower thanthe one in the scheme [206]+ Resistance to replay attackman-in-the-middle attack anddenial of service (DoS) attackminus Privacy-preserving is notanalyzed compared to theGLARM scheme [61]minus Lack nonrepudiationcompared to the PBA scheme in[64]

Shao et al(2016) [63]

VANET with some partiesincluding central authoritytracing manager manyRSUs and many OBUs

Guarantee unforgeabilityanonymity and traceability

Initialization stageRegistration stageJoin stageSign stageVerify stageTrace stage

+ Efficient in terms of thecomputational cost of threeoperations namely InitializationRegistration and Trace+ Can prevent replay attacksminus No comparison with otherschemesminusThe communication overheadis not studiedminus Lack nonrepudiationcompared to the PBA scheme in[64]

Lyu et al (2016)[64]

VANET with dividemessages into two types (1)single-hop beacons and (2)multi-hop traffic data

Guarantee some propertiessuch as timelyauthenticationnonrepudiation packetlosses resistant and DoSattacks resistant

(i) Chained keysgeneration(ii) Position prediction(iii) Merkle hash treeconstruction(iv) Signature generation

+ Considers the nonrepudiation+The computational costreduces with the increasing oftime frame+ Can resist packet losses+ Maintain high packetprocessing rate with low storageoverheadminus Privacy-preserving is notanalyzed compared to theGLARM scheme [61]

Zhang et al(2016) [65]

Trusted authority (TA) anumber of RSUs andvehicles

Guarantee the conditionalunlinkability idealtamper-proof device (TPD)freeness key escrowfreeness

(i) Member secretsgeneration(ii) Vehicle sign(iii) Message verificationand signature storage(iv) Trace internalpseudo-identity (IPID)and authentication keyupdate(v) On-Line update

+ Efficient in terms of messageauthentication delay on average+ Considers privacy preserving+ Resistance to the side-channelattack false messages attackdenial-of-service (DoS) attackand Sybil attack+ Efficient compared to theECDSA protocol in [163] andmore efficient than the IBAscheme in [52] on averageminus Lack nonrepudiationcompared to the PBA scheme in[64]


Table 18 Continued



VANET with four mainentities ie key generatorcenter (KGC) trafficmanagement authority(TMA) RSUs and vehicles

Guarantee some propertiessuch as messageauthenticationnonrepudiation messageconfidentiality privacy andtraceability

(i) System setup(ii) Protocol for STP andSTK distribution(iii) Protocol for commonstring synchronization(iv) Protocol for vehicularcommunications

+ Efficient in terms of the averagemessage delay and theverification delay+ Efficient in terms ofverification delay compared tothe scheme in [166]+ Considers the nonrepudiation+ Resistance to attacks namelymessage reply messagemodification movementtrackingminus Location privacy is notconsidered

Dolev et al(2016) [66]

The vehicle network isdivided into the controllerarea network (CAN) localinterconnect network(LIN) and media orientedsystem (MOST)

Ensure thecountermeasures againstthe Man-in-the-Middleattack under the vehicleauthentication

(i) System settings(ii) Certificate authority(iii) Vehicular attributes

+ Efficient in terms of iterationcost compared to the existingAuthenticated Key Exchange(AKE) protocols such as ISO-KE[207] and SIGMA [208]+ Resistance to attacks namelyMan-in-the-Middle attack andimpersonation attackminus Privacy-preserving is notanalyzed compared to theGLARM scheme [61]

Chan andZhou (2014)[48]

Smart grid electric vehicleecosystem

Provides assurance of thedigital identity and thedevicersquos controllability inthe physical domain

(i) Communicationsettings(ii) Cyber-physical deviceauthentication

+ Resistance to substitutionattacksminus No comparison with otherschemesminusThe average message delay andthe verification delay are notevaluated

53 Authentication Protocols for IoE The surveyed papersof authentication protocols for Internet of Energy (IoE) asshown in Table 19 are published between 2011 and 2016We noted here that we have reviewed some authenticationprotocols proposed for secure smart grid communicationsin our survey in [219] namely the schemes in [236] Inthis subsection we will review only the works that are notreviewed in the survey [219]

To provide multicast authentication in smart grid Li andCao [28] proposed the scheme Tunable Signing and Verifica-tion (TSV) Specifically TSV combines Heavy signing lightverification (HSLV) and Light Signing Heavy Verification(LSHV) to achieve a flexible tradeoff between the two TSVcan reduce the storage cost but the privacy-preserving is notdiscussed and the reportsrsquo confidentiality and integrity are notconsidered compared to the scheme [49] The smart metersare planning to reduce the time intervals to 1min or evenless For this Li et al [49] developed a Merkle-tree-basedauthentication scheme to minimize computation overheadon the smart meters The work [49] is efficient in terms of

computation complexity of the HAN user and the neigh-borhood gateway compared to the RivestndashShamirndashAdleman(RSA)-based authentication scheme [237]Therefore Li et al[138] fixed the single-point failure in smart grid by proposingthe idea of deploying a fault tolerance architecture to executethe authentication approach without any additional configu-ration or setup Based on both main processes namely (1)batch verification and trinary diagnose TreeBatch and (2)signature amortization for Package Blocks the work [138] canlegalize the data aggregation with tremendously less signingand verification operations

Nicanfar et al [139] addressed the key management forunicast andmulticast communications in the smart gridThework [154] proposed a scheme for the mutual authenticationbetween the smart grid utility network and Home AreaNetwork smart meters called SGAS-I which can increaseperformance of the key management and does not causeany security drawback Based on the multicast key supportphase SGAS-I can provide simplicity and low overheadbut the reportsrsquo confidentiality and integrity are considered


Table 19 Summary of authentication protocols for IoE

Prot Network model Goals Main processes Performances (+) and limitations (minus)

Li and Cao(2011) [28]

Smart Grid with widemulticastapplications namelywide area protectiondemand-responseoperation and controland in-substationprotection

Provide multicastauthentication

(i) Key generation(ii) Signing(iii) Verification

+ Efficient in terms of hash or one-wayfunction invocations compared to the scheme[209]+ Resistance to message forgery attacks+ Can reduce the storage costminus Privacy-preserving is not discussedminusThe reportsrsquo confidentiality and integrity arenot considered compared to the scheme [49]

Li et al (2014)[49]

Communicationbetween the homearea networks(HANs) and theneighborhoodgateway using WiFitechnology

(i) Detecting thereplay attacks(ii) Providingauthentication for thesource of electricityconsumption reports(iii) Guarantees thereportsrsquoconfidentiality andintegrity

(i) System initialization(ii) Report generation(iii) Neighborhoodgateway authentication

+ Efficient in terms of computation complexityof the HAN user and the neighborhoodgateway compared to the RSA-basedauthentication scheme+ Efficient in terms of communicationoverhead between the HAN user and theneighborhood gateway compared to theRSA-based authentication scheme+ Resistance to attacks namely replay attackmessage injection attack message analysisattack and message modification attack+ Guarantees the reportsrsquo confidentiality andintegrity compared to the scheme [28]minusThe routing attacks are not considered suchas wormhole attack

Li et al (2012)[138]

The smart grid withpower generationpower transmissionand powerdistribution

Providing theauthentication forpower usage dataaggregation inNeighborhood AreaNetwork (NAN) withfault tolerancearchitecture

(i) Key generation(ii) Signature generation(iii) Batch verificationand trinary diagnoseTreeBatch(iv) Signatureamortization for PackageBlocks

+ Makes significant performance gains in termsof the communication and computation cost+ Considers the fault diagnosisminus No threat model presented

Nicanfar et al(2011) [139]

(i) The datacommunication inoutside of the HomeArea Network (HAN)(ii) Some smartmeters and a utilityserver under awireless meshnetwork topology

Providing mutualauthenticationscheme to preventbrute-force attacksreplay attacksMan-In-The-Middle(MITM) attack andDenial-of-Service(DoS) attacks

(i) Initialization(ii) Ongoingmaintenance or Shortperiod key refreshment(iii) Long period keyrefreshment(iv) Multicast keysupport

+ Can provide simplicity and low overhead+ Resistance to attacks namely brute-forceattacks replay attacks Man-In-The-Middle(MITM) attack and Denial-of-Service (DoS)attacks+ Can provide secure key managementminusThe reportsrsquo confidentiality and integrity areconsidered compared to the scheme [49]

Chim et al(2011) [140]

Smart grid networkwith three basiclayers namely powergeneratorssubstations andsmart meters andsmart appliances

Guarantee themessageauthenticationidentity privacy andtraceability

(i) Preparation module(ii) Pseudo-identitygeneration module(iii) Signing module(iv) Verification module(v) Tracing module

+ Requires only an additional 368msec forHMAC signature verification at a substation+ Efficient in overall normal traffic success ratewhen under attack+The message overhead is only 20 bytes perrequest messageminusThe routing attacks are not considered suchas wormhole attackminus Storage costs are not consideredminus No comparison with other schemes

Fouda et al(2011) [141]

Smart grid with thepower DistributionNetwork (DN) theTransmissionSubstation (TS) and anumber ofDistributionSubstations (DSs)

Providing mutualauthentication andachieving messageauthentication in alight-weight way

(i) Key generation(ii) Message generation(iii) Hash-based messageauthentication

+ Efficient in terms of communicationoverhead and message decryptionverificationdelay compared to ECDSA-256+ Resistance to attacks namely replay attackchosen-plaintext attack and collision attackminus Location privacy is not consideredminus Identity privacy and traceability are notconsidered compared to the scheme [140]


Table 19 Continued



Multigatecommunicationnetwork proposed in[210]

Providing mutualauthentication andkey managementmechanisms

(i) SGMA scheme(System setup Mutualauthentication Scheme)(ii) SGKM protocol (Keyrefreshment Multicastkey mechanismBroadcast keymechanism)

+ Can prevent the adversary fromcontinuing the successful attack+ Can prevent various attacks whilereducing the management overheadminus Storage costs are not consideredminus Lack nonrepudiation compared to thePBA scheme in [64]

Chim et al(2015) [55]

Smart grid networkbased on hierarchicalarchitecture ieHANs BANs NANs

Providing theprivacy-preservingrecording andgateway-assistedauthentication

(i) Preparation phase(ii) Power plansubmission phase(iii) Power planprocessing phase(iv) Reconciliationphase(v) System master secretupdating phase

+The message filtering at gateway smartmeters can be helpful in reducing the impactof attacking traffic+The privacy preserving and traceability areconsideredminus No comparison with other schemesminus Distributed denial of service (DDoS)attacks is not considered

Mahmood etal (2016) [67]

The system model ishomogeneous to themodel in [49]

Detect and omit someattacks namelyreplay false messageinjection messageanalysis andmodification attacks

(i) Initialization(ii) Authentication(iii) Messagetransmission

+ Efficient in terms of communication costand computation cost compared to theschemes [30 35]+ Resistance to attacks namely replay falsemessage injection message analysis andmodification attacks+The reportsrsquo confidentiality and integrityare consideredminus Location privacy is not considered

compared to the scheme [49] To guarantee the messageauthentication with identity privacy and traceability Chim etal [140] proposed a scheme called PASS for the hierarchicalstructure of a smart grid The PASS scheme focuses onlyon the substation-to-consumer subsystem where the realidentity of any smart appliance can only be known by thecontrol center using the concept of pseudo identity Similarto the PASS scheme Fouda et al [141] proposed a schemethat can only provide an authenticated and encrypted channelfor the late successive transmission but can also establisha semantic-secure shared key in the mutual authenticationenvironment The work in [141] is efficient in terms of com-munication overhead and message decryptionverificationdelay compared to ECDSA-256 but the identity privacy andtraceability are not considered compared to the scheme [140]

In order to provide the mutual authentication betweensmart meters and the security and authentication serverin the smart grid using passwords Nicanfar et al [142]proposed a mutual authentication scheme and a key man-agement protocol called SGMAand SGKM respectivelyTheSGMA scheme concentrates on data communications overthe advanced metering infrastructure (AMI) outside of theHAN domain where each node has a unique ID and eachsmart meter has a unique serial number SN embedded by themanufacturer and an initial secret password On the otherhand the SGKM protocol concentrates on node-to-nodesecure communications where the nodes have the appropri-ate privatendashpublic keys to be used for unicast Based on themulticast key mechanism the SGMA scheme can prevent

various attacks while reducing themanagement overhead butlack nonrepudiation compared to the PBA scheme in [64]Shim et al [55] consider a smart grid network based onhierarchical architecture that is HANs BANs and NANsThe work [55] proposed privacy-preserving recording andgateway-assisted authentication of power usage informationThe message filtering at gateway smart meters can be helpfulin reducing the impact of attacking traffic Similar to thescheme [55] Mahmood et al [67] proposed a lightweightmessage authentication scheme Based on two main pro-cesses namely (1) authentication and (2) message transmis-sion the scheme [67] can detect and omit some attacksnamely replay false message injection message analysisand modification attacks In addition the scheme [67] isefficient in terms of communication cost and computationcost compared to the schemes [30 35] but the locationprivacy is not considered

54 Authentication Protocols for IoS The surveyed papersof authentication protocols for Internet of Sensors (IoS) asshown in Table 20 are published in 2016 We noted here thatwe have reviewed some authentication protocols proposedfor ad hoc social network (an application of WSN) in oursurvey in [220] In this subsection we will review only theworks that are not reviewed in the survey [220] and thearticles published in 2016 related to authentication protocolsfor IoS For more details about the articles published before2016we refer the reader to six surveys published in 2013 2014and 2015 namely [238ndash243]


Table 20 Summary of authentication protocols for IoS (Published in 2016)


Kumari et al(2016) [68]

Wireless sensor network(WSN) with the serviceseeker users sensingcomponent sensor nodes(SNs) and the serviceprovider base-station orgateway node (GWN)

Providing mutualauthentication withforward secrecy and wrongidentifier detectionmechanism at the time oflogin

(i) Initialization phase(ii) User registration phase(iii) Login phase(iv) Authentication amp keyagreement phase(v) Password change phase

+The user is anonymous+ Resistance to attacks namely userimpersonation attack passwordguessing attack replay attack stolenverifier attack smart card lossattack session-specific temporaryinformation attack GWN Bypassattack and privileged insider attack+ Provides a secure session-keyagreement and forward secrecy+ Provides freely passwordchanging facility+ Efficient in unauthorized logindetection with wrong identity andpasswordminusThe data integrity is notconsidered

Chung et al(2016) [69]

Wireless sensor networksfor roaming service

Providing an enhancedlightweight anonymousauthentication to resolvethe security weaknesses ofthe scheme [60]

(i) Registration phase(ii) Login andauthentication phase(iii) Password change phase

+ Considers anonymity hop-by-hopauthentication and untraceability+ Resistance to attacks namelypassword guessing attackimpersonation attack forgeryattack known session key attackand fair key agreementminus Location privacy is not considered

Gope andHwang (2016)[71]

Real-time data access inWSNs

Ensuring the useranonymity perfect forwardsecrecy and resiliency ofstolen smart card attacks

(i) Registration phase(ii) Anonymousauthentication and keyexchange phase(iii) Password renewalphase(iv) Dynamic nodeaddition phase

+ Considers the user anonymityand untraceability+ Provides perfect forward secrecy+ Security assurance in case of lostsmart card+ Resilience against node captureattack and key compromiseimpersonation AttackminusThe average message delay and theverification delay are not evaluated

Chang and Le(2016) [73]

Users sensor nodes andgateway node in WSN

Providing mutualauthentication and perfectforward secrecy

(i) Registration phase(ii) Authentication phase(iii) Password changingphase

+ Considers the session keysecurity perfect forward secrecyand user anonymity+ Resistance to attacks namelyreplay attack and smart card lostattack+ Efficient in terms of computationcost in the authentication phasescompared to the schemes[42 50 51 211]minus Privacy-preserving is notanalyzed compared to the GLARMscheme [61]

Jiang et al(2016) [74]


Providing mutualauthentication anonymityand untraceability

(i) Registration phase(ii) Login andauthentication phase

+ Provides mutual authenticationsession key agreement useranonymity and user untraceability+ Resistance to attacks namelysmart card attack impersonationattack modification attackman-in-the-middle attack andtracking attackminusWormhole attack and blackholeattack are not considered


Table 20 Continued


Farash et al(2016) [75]


Providing the userauthentication withtraceability protection andsensor node anonymity

(i) Predeployment phase(ii) Registration phase(iii) Login andauthentication phase(iv) Password change phase

+ Efficient in terms ofcommunication computation andstorage cost compared to thescheme [51]+ Resistance to attacks namelyreplay attack privileged-insiderattack man-in-the-middle attackinsider and stolen verifier attacksmart card attack impersonationattack bypassing attack manylogged-in users with the samelogin-id attack password changeattack and DoS attackminusWormhole attack and blackholeattack are not considered



Providing the mutualauthentication withtraceability and anonymity

(i) Offline sensor noderegistration phase(ii) User registration phase(iii) Login phase(iv) Authentication and keyagreement phase(v) Password update phase(vi) Dynamic sensor nodeaddition phase

+ Efficient in terms of end-to-enddelay (EED) (in seconds) andthroughput (in bps)+ Efficient in terms of computationcost in login and authenticationphases compared to both schemesTurkanovic et al [51] and Farash etal [75]+ Resistance to attacks namelyreplay attack stolen smart cardattack privileged-insider attackoffline password guessing attackimpersonation attack and sensornode capture attackminusWormhole attack and blackholeattack are not consideredminus Lack nonrepudiation compared tothe PBA scheme in [64]

Sun et al(2016) [145]

Multicast communicationsin WSNs including sinkand many groups and eachgroup has a powerful nodeand many low ordinarynodes

Providing the broadcastauthentication andenhanced collusionresistance

(i) Initialization(ii) Broadcast(iii) Group keysrsquo recoveryand pairwise keysrsquoupdating(iv) Node addition(v) Node revocation

+ Collusion resistance+ Resistance to attacks namelyPKE-attack and PF-attackminusThe end-to-end delay andthroughput are not evaluatedcompared to the scheme [76]minus Replay attack is not considered



Achieving mutualauthentication among thecommunicating agents withuser anonymity anduntraceability

(i) Registration phase(ii) Login phase(iii) Authentication phase(iv) Password change phase

+ Resistance to attacksstolen-verifier attack guessingattack impersonation attackmodification attackman-in-the-middle attack andreplay attackminusThe end-to-end delay andthroughput are not evaluatedcompared to the scheme [76]minus Collusion resistance is notconsidered compared to the scheme[145]

Kumari et al [68] reviewed and examined both schemesproposed by Li et al in [42] and He et al in [57] for itssuitability to WSNs Based on the results of this analysisthe authors proposed a chaotic maps based user-friendlyauthentication scheme for WSN with forward secrecy and

wrong identifier detection mechanism at the time of loginThe idea is to establish a session key between user and sensornode (SN) using extended chaotic maps The scheme ofKumari et al [68] is efficient in unauthorized login detectionwithwrong identity andpassword but the data integrity is not


considered Similar to [68] Chung et al [69] reviewed andexamined the scheme [60] Based on the security weaknessesof the scheme [60] the work [69] proposed an enhancedlightweight anonymous authentication scheme for a scalablelocalization roaming service in WSN Using three phasesnamely (1) registration phase (2) login and authenticationphase and (3) password change phase the work [69] canprovide anonymity hop-by-hop authentication and untrace-ability but location privacy is not considered

Jan et al [143] proposed an extremely lightweightpayload-based mutual authentication called PAWN for thecluster-based hierarchical WSNThe PAWN scheme is basedon two main phases namely (1) token-based cluster headelection and (2) payload-based mutual authentication Withphase 1 the higher-energy nodes perform various admin-istrative tasks such as route discovery route maintenanceand neighborhood discovery The authentication procedureis accomplished using the cooperative neighbor times neighbor(CNN) [244] that is session initiation server challengeclient response and challenge and server response ThePAWN scheme is efficient in terms of average energy con-sumption andHandshake duration compared to the LEACH-C scheme in [245] and the SecLEACH scheme [246] butthe privacy preservation is not analyzed compared to othermethods such as the GLARM scheme [61] Based on thesecurity weaknesses of the scheme [51] Amin andBiswas [70]proposed a secure lightweight scheme for user authenticationand key agreement in multigateway based WSNThe scheme[70] is efficient in terms of computational cost storage andcommunication cost compared to the schemes [31 36 41 4551] In addition the scheme [70] can providemuch less energyconsumption of the sensor nodes and user anonymity

For the security of real-time data access in WSNs Gopeand Hwang [71] proposed an authentication protocol toensure the user anonymity perfect forward secrecy andresiliency of stolen smart card attacks The protocol [71]is efficient in terms of computational and communicationcost compared to the schemes [31 41 72 190 247] Basedon the security weaknesses of the scheme [190] Das [72]proposed a secure and robust temporal credential-basedthree-factor user authentication scheme The scheme [72]uses a biometric password and smart card of a legal userThe simulation results of the scheme [72] demonstrate thatit is efficient in terms of computational and communicationoverhead compared to the schemes [41 248 249] Based onthe weaknesses in Turkanovic et alrsquos protocol [51] Chang andLe [73] proposed a flexible authentication protocol using thesmart card for WSNs which operates in two modes namely(1) providing a lightweight authentication scheme and (2)an advanced protocol based on ECC which provides perfectforward secrecy Both these two modes are efficient in termsof computation cost in the authentication phases comparedto the schemes [42 50 51 211]

Trying to deal with the weaknesses of the scheme pre-sented in [57] Jiang et al [74] proposed an untraceable two-factor authentication scheme based on elliptic curve cryptog-raphy The scheme [74] is efficient in terms of computationalcost compared to previous schemes [31 50 57 211 250] butthe performance of the system under common attacks such

as the wormhole attack and the blackhole attack is not pre-sented Based on the weaknesses in the scheme [51] Farashet al [75] proposed an efficient user authentication and keyagreement scheme for heterogeneouswireless sensor networktailored for the Internet of Things environment The scheme[75] is efficient in terms of communication computationand storage cost compared to the scheme [51] but again theperformance of the system under the wormhole attack or theblackhole attack is not presented Based on the weaknesses inAmin and Biswasrsquos scheme [70] Srinivas et al [144] proposeda user authentication scheme for multigateway WSNs Thescheme [144] is efficient in terms of communication overheadduring the login and authentication phase compared to theschemes [21 70] but the performance of the system interms of privacy preservation is not analyzed compared toprevious methods such as the GLARM scheme [61] Similarto both schemes [74 144] Kumari et al [76] pointed outthat the scheme of Farash et al [75] is insecure against someattacks The work presented in [76] especially is efficient notonly in terms of end-to-end delay (EED) (in seconds) andthroughput (in bps) but also in terms of computation cost inlogin and authentication phases compared to both schemesby Turkanovic et al [51] and Farash et al [75]

Sun et al [145] considered the multicast communicationsin WSNs including sink and many groups where eachgroup may have a powerful node and many low ordinarynodes The powerful node acts as the group manager (GM)and is responsible for network security management suchas key issues updating revocation and intrusion detectionThen the authors reviewed and examined the scheme [188]in order to propose a scheme that considers the forwardsecurity backward security and collusion resistance Basedon the idea of access polynomial the Sun et al scheme [145]is efficient in terms of storage computation and commu-nication overhead but the replay attack is not consideredJiang et al proposed a scheme [77] that can achieve mutualauthentication among the communicating agents with useranonymity and untraceability In addition the Jiang et alscheme [77] is efficient in terms of computational costcompared to the schemes in [31 50 211 250] but the collusionresistance is not considered compared to the scheme in [145]

Based on the weaknesses in the scheme [251] Wu etal [146] proposed an improved three-factor authenticationscheme for WSNs which can be resistant to the desyn-chronization attack Das et al [147] reviewed the recentlyproposed ChangndashLersquos two protocols [73] and then showedthat their protocols are insecure against some known attacksLiu and Chung [148] proposed a secure user authenticationscheme for wireless healthcare sensor networks which isefficient in terms of computation cost compared to bothschemes in [252 253] Gope et al [254] proposed a specialidea for resilience of DoS attacks in designing anonymoususer authentication protocol Combining three techniquesnamely smart card password and personal biometrics Daset al [197] proposed a three-factor user authentication andkey agreement scheme based on multigateway WSN archi-tecture The scheme [197] is efficient in terms of computa-tional communication and energy costs Benzaid et al [255]proposed an accelerated verification of digital signatures


generated by BNN-IBS [256] which is an idea inspired by theacceleration technique of Fan and Gong [257]

6 Open Issues

61 M2M Open Issues M2M communications can facilitatemany applications like e-health smart grids industrialautomation and environmental monitoring but on the sametime face various security threats and trust issues In e-health especially authentication of the devices must berobust to attacks that could threaten the correct exchangeof information and consequently the life of the patientIn order to safely share and manage access to informa-tion in the healthcare system it is essential to be able toauthenticate users including organizations and people InAustralia authentication is achieved through the use of digitalcertificates that conform to the Australian Governmentendorsed Public Key Infrastructure (PKI) standard throughthe National Authentication Service for Health (NASH) butthorough research of the resistance to attacks of this and othersimilar systems is needed in order to reassure its robustnessScalability and Heterogeneity are a rather general problemwhen dealing with M2M communication of devices thatcome from different vendors and using different operatingsystems Solutions that focus only to Android devices [137]cannot guarantee end-to-end security of the system

62 IoV Open Issues Although a number of authenticationprotocols have been proposed recently which are capable ofguaranteeing authentication for a network of vehicles thereare still open issues that need to be addressed by the researchcommunity

621 Autonomous Driving Until now anonymity of platoonmembers has been addressed in [54] which is capable ofproviding strong anonymous access authentication to themembers of the platoon Taking one step further and dealingwith full automated vehicles that will be able to createplatoons on the fly with no central entity or trust authorityin reach novel authentication methods where vehicles canrun by themselves must be developed This could be doneusing several techniques Onemethod would be to use digitalsignatures where each vehicle holds its own signing key andcan verify its identity by signing challenges combined witha defense mechanism that can face MITM attacks Othermethods could be the use of the trust levels of every vehicleusing methods similar to [258]

622 Heterogeneous Vehicular Networking The designdevelopment and deployment of vehicular networksare boosted by recent advances in wireless vehicularcommunication techniques such as dedicated short-rangecommunications (DSRC) Long-Term Evolution (LTE)IEEE 80211p andWorldwide Interoperability for MicrowaveAccess (WiMax) Novel protocols that can be deployedon all these communication channels and can guaranteeauthentication under attacks that can be initiated fromeach one of these networks are an area of future researchSafeguarding one communication channel without dealing

with the threats that all these networks face will leave the IoVvulnerable to several kinds of attacks against authentication

623 Social Internet of Vehicles Social Internet of Vehicles(SIoV) describes the social interactions both among vehicles[259] and among drivers [260] Ensuring authentication inthe communication among vehicles cannot guarantee fullprotection of identities of entities if the social notion ofcommunication is neglected [125] Future authentication-enhancing technologies for SIoVs should be based on provenauthentication-enhancing technologies for social networksand vehicular networks

63 IoE Open Issues Based on the definition of the Internetof Energy as an integrated dynamic network infrastructurebased on standard and interoperable communication proto-cols that interconnect the energy network with the Internetallowing units of energy to be dispatchedwhen andwhere it isneeded it is easily understood that authentication in the IoEenvironment is not an easy problem to solve IoE combinesM2M V2G IIoT (industrial Internet of things) Smart homeautomation cloud services and IoS It would be better todefine IoE as an application of the IoT on the Energy domainAuthentication on the IoE domain cannot be reassured with-out dealing with each of the aforementioned subdomainsSecurity [261] and hardware [262] authentication techniquesalong with solutions dealing with middleware security [263]must be combined

64 IoS Open Issues The major problems that the IoSnetworks have to face are energy efficiency and security assur-ance of the sensors Intrusion Detection Systems (IDSs) andenergy efficient mechanisms are not thoroughly investigatedand resolved in the surveyed authentication protocols for theIoS Raza et al [264] proposed an idea based on real-timeintrusion detection for the IoT called SVELTE Mechanismsthat can extend the SVELTE scheme for the IoS in order tobe energy efficient would be a possible research directionHence future works addressing both security mainly IDSsand energy will have an important contribution for theauthentication protocols In addition we believe furtherresearch is needed to develop a new framework for combiningintrusion detection systems and authentication protocols fordetecting and avoiding attacks in IoS

65 Pattern Recognition and Biometrics for the IoT Hybridauthentication protocols are based on two methods foridentifying an individual including knowledge-based (egthe passwords) and token-based (eg the badges) Eachmethod has its weakness that is (1) the password can beforgotten or guessed by an adversary and (2) the badgecan be lost or stolen Nevertheless the safest way is theuse of biometric characteristics because two people cannotpossess exactly the same biometric characteristic Hencefuture works addressing pattern recognition authenticationtechniques along with biometrics will have an importantcontribution in improving authentication in the IoT Recentlynew promising efforts that apply biometrics on IoT have beenproposed [265] and the term of Internet of biometric things


(IoBT) has been introduced [266] Biometric technology onthe other hand raises privacy and ethical issues that need to betaken in mind when designing new authentication protocolsespecially for applications that deal with critical data [267]

66 Authentication for the IoT Applications in 5G Thedevelopment of 5G networks is driven by IoT connectivitywhere the IoT applications have been categorized into twoclasses massive machine-type communications (mMTC)and ultrareliable low-latency communications (URLLC) asdiscussed by Schulz et al [268] As mobile devices will beconnected to the network all the time the IoT applicationscan more easily be tracked down and are more vulnerable toseveral types of attacks like impersonation eavesdroppingman-in-the middle denial of service replay and repudiationattack [269] One possible future direction is to develop anauthentication protocol for the IoT applications in 5G

67 Lessons Learned From the threat models in M2M IoVIoE and IoSwe found thirty-five attacks discussed by the sur-veyed protocolsTherefore we were able to classify the formalsecurity verification techniques into five techniques namelyBAN-logic analysis by process Game Theory Automatedreasoning (ProVerif) and Automated Validation (AVISPA)In addition based on the cryptosystems we were able toclassify the authentication protocols for the IoT into threecategories namely symmetric-cryptosystembased protocolsasymmetric-cryptosystem-based protocols and hybrid pro-tocols

After conducting a comprehensive survey of authenti-cation protocols we see that the reliability of an authen-tication protocol depends not only on the effectiveness ofthe cryptography method used against attacks but also onthe computation complexity and communication overheadTherefore in order to guarantee authentication between themachines for the IoT we invite well-positioned researchersand practitioners to propose authentication frameworks thatcover not only one but three layers namely the applicationlayer the network layer and the sensing layer In this paperwe also see a need for a comprehensive survey for privacy-preserving schemes for the IoT under four environmentsincluding M2M IoV IoE and IoS

Authentication protocols for the IoT may be improvedin terms of (1) addressing both the authentication andprivacy problem (2) developing efficient IDSs (3) improvingthe computation complexity of the proposed methods (4)improving the communication overhead of the methods (5)developing of formal security verification techniques (6)accounting of the process of detecting and avoiding attacksand (7) capturing of experts opinion in the field of computersecurity

7 Conclusion

In this paper a structured comprehensive overview of authen-tication protocols for the IoT is presented These protocolscan be categorized based on the target environment forexample Machine to Machine Communications (M2M)

Internet of Vehicles (IoV) Internet of Energy (IoE) andInternet of Sensors (IoS) Major threats countermeasuresand formal security verification techniques used by state-of-the-art authentication protocols are presented A side-by-side comparison in a tabular form for the current state-of-the-art of authentication protocols proposed for M2M IoVIoE and IoS is also provided Based on this analysis futureresearch directions are given Authentication protocols forthe IoTmay be improved in terms of being able to cover bothauthentication and privacy and be more efficient in termsof computation complexity and communication overhead aslong as they are able to cooperate with other mechanisms fordetecting and avoiding attacks in the IoT

Acronyms

3GPP 3rd Generation Partnership ProjectAES Advanced encryption standardAKA Authentication and key agreement

protocolAMACs Aggregate message authentication codesAVISPA Automated Validation of Internet Security

Protocols and ApplicationBAN-logic Burrows-Abadi-Needham LogicBTS Base Transceiver StationDoS Denial of Service attackECC Elliptic Curve CryptographyECDH Elliptic Curve Diffie-HellmanGPS Global Positioning SystemHANs Home area networksHMAC Keyed-hashing for message authenticationHSLV Heavy signing light verificationIBC ID-based cryptographyIIoT Industrial Internet of ThingsIoBT Internet of biometric thingsIoE Internet of EnergyIoS Internet of SensorsIoT Internet of ThingsIoV Internet of VehiclesLSHV Light signing heavy verificationM2M Machine to Machine CommunicationsMAC Message Authentication CodeMD5 Message Digest 5MHT Merkle Hash TreeMITM Man-in-the-middle attackMS Mobile StationMTC Machine-type CommunicationPKI Public Key InfrastructurePMIP Proxy Mobile IPRFID Radio Frequency IdentificationRSUs Road Side UnitsSDON Software Defined Optical NetworkSHA Secure Hash AlgorithmSIoV Social Internet of VehiclesVANET Vehicular ad hoc networkWiMAX Worldwide Interoperability for Microwave

AccessWoT Web of ThingsWSN Wireless Sensor Network


Conflicts of Interest

The authors declare that they have no conflicts of interest

References

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[2] IBM IoT httpwwwibmcominternet-of-things[3] ldquoWatson IoTrdquo httpwwwibmcominternet-of-thingslearn

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[8] M Gerla E-K Lee G Pau and U Lee ldquoInternet of vehiclesfrom intelligent grid to autonomous cars and vehicular cloudsrdquoin Proceedings of the IEEE World Forum on Internet of Things(WF-IoT rsquo14) pp 241ndash246 March 2014

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[25] Y-L Huang C-Y Shen and S W Shieh ldquoS-AKA a provableand secure authentication key agreement protocol for UMTSnetworksrdquo IEEE Transactions on Vehicular Technology vol 60no 9 pp 4509ndash4519 2011

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[30] M M Fouda Z M Fadlullah N Kato R Lu and X S ShenldquoA lightweight message authentication scheme for smart gridcommunicationsrdquo IEEE Transactions on Smart Grid vol 2 no4 pp 675ndash685 2011

[31] H-L Yeh T-H Chen P-C Liu T-H Kim and H-W WeildquoA secured authentication protocol for wireless sensor networksusing Elliptic Curves Cryptographyrdquo Sensors vol 11 no 5 pp4767ndash4779 2011

[32] J Cao M Ma and H Li ldquoA group-based authentication andkey agreement for MTC in LTE networksrdquo in Proceedings of theIEEEGlobal Communications Conference (GLOBECOM rsquo12) pp1017ndash1022 Anaheim Calif USA December 2012

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[34] A Fu S Lan B Huang Z Zhu and Y Zhang ldquoA novel group-based handover authentication scheme with privacy preser-vation for mobile WiMAX networksrdquo IEEE CommunicationsLetters vol 16 no 11 pp 1744ndash1747 2012

[35] R Sule R S Katti and R G Kavasseri ldquoA variable lengthfast message authentication code for secure communication insmart gridsrdquo in Proceedings of the 2012 IEEE Power and EnergySociety General Meeting PES 2012 usa July 2012

[36] A K Das P Sharma S Chatterjee and J K Sing ldquoA dynamicpassword-based user authentication scheme for hierarchicalwireless sensor networksrdquo Journal of Network and ComputerApplications vol 35 no 5 pp 1646ndash1656 2012

[37] C Lai H Li R Lu R Jiang and X Shen ldquoLGTH alightweight group authentication protocol for machine-typecommunication in LTE networksrdquo in Proceedings of the IEEEGlobal Communications Conference (GLOBECOM rsquo13) pp 832ndash837 December 2013

[38] C Lai H Li R Lu and X Shen ldquoSE-AKA a secure andefficient group authentication and key agreement protocol forLTE networksrdquo Computer Networks vol 57 no 17 pp 3492ndash3510 2013

[39] S Cespedes S Taha and X Shen ldquoA multihop-authenticatedproxy mobile IP scheme for asymmetric VANETsrdquo IEEE Trans-actions on Vehicular Technology vol 62 no 7 pp 3271ndash32862013

[40] AWasef and X S Shen ldquoEMAP Expedite message authentica-tion protocol for vehicular ad hoc networksrdquo IEEE Transactionson Mobile Computing vol 12 no 1 pp 78ndash89 2013

[41] K Xue C Ma P Hong and R Ding ldquoA temporal-credential-based mutual authentication and key agreement scheme forwireless sensor networksrdquo Journal of Network and ComputerApplications vol 36 no 1 pp 316ndash323 2013

[42] C-T Li C-Y Weng and C-C Lee ldquoAn advanced temporalcredential-based security scheme with mutual authenticationand key agreement for wireless sensor networksrdquo Sensors vol13 no 8 pp 9589ndash9603 2013

[43] Q Jiang J Ma G Li and L Yang ldquoAn enhanced authenticationscheme with privacy preservation for roaming service in globalmobility networksrdquoWireless Personal Communications vol 68no 4 pp 1477ndash1491 2013

[44] F Wen W Susilo and G Yang ldquoA secure and effectiveanonymous user authentication scheme for roaming service inglobal mobility networksrdquo Wireless Personal Communicationsvol 73 no 3 pp 993ndash1004 2013

[45] M Turkanovic andMHolbl ldquoAn improved dynamic password-based user authentication scheme for hierarchical wirelesssensor networksrdquo Elektronika ir Elektrotechnika vol 19 no 6pp 109ndash116 2013

[46] C Lai H Li R Lu R Jiang and X Shen ldquoSEGR A secureand efficient group roaming scheme for machine to machinecommunications between 3GPP and WiMAX networksrdquo inProceedings of the 2014 1st IEEE International Conference onCommunications ICC 2014 pp 1011ndash1016 aus June 2014

[47] C Lai H Li X Liang R Lu K Zhang and X Shen ldquoCPALA conditional privacy-preserving authentication with accesslinkability for roaming servicerdquo IEEE Internet ofThings Journalvol 1 no 1 pp 46ndash57 2014

[48] A C-F Chan and J Zhou ldquoCyberndashPhysical Device Authen-tication for the Smart Grid Electric Vehicle Ecosystemrdquo IEEEJournal on Selected Areas in Communications vol 32 no 7 pp1509ndash1517 2014

[49] H Li R Lu L Zhou B Yang andX Shen ldquoAn efficientMerkle-tree-based authentication scheme for smart gridrdquo IEEE SystemsJournal vol 8 no 2 pp 655ndash663 2014

[50] Y Choi D Lee and J Kim ldquoSecurity enhanced user authentica-tion protocol for wireless sensor networks using elliptic curvescryptographyrdquo Sensors vol 14 no 6 pp 10081ndash10106 2014

[51] M Turkanovic B Brumen and M Holbl ldquoA novel userauthentication and key agreement scheme for heterogeneous adhoc wireless sensor networks based on the Internet of Thingsnotionrdquo Ad Hoc Networks vol 20 pp 96ndash112 2014

[52] L Zhang C Hu Q Wu J Domingo-Ferrer and B QinldquoPrivacy-preserving vehicular communication authenticationwith hierarchical aggregation and fast responserdquo Institute ofElectrical and Electronics Engineers Transactions on Computersvol 65 no 8 pp 2562ndash2574 2016

[53] X Sun SMen C Zhao andZ Zhou ldquoA security authenticationscheme in machine-to-machine home network servicerdquo Secu-rity and Communication Networks vol 8 no 16 pp 2678ndash26862015

[54] C Lai R Lu and D Zheng ldquoSGSA Secure group setup andanonymous authentication in platoon-based vehicular cyber-physical systemsrdquo Lecture Notes in Computer Science (includingsubseries Lecture Notes in Artificial Intelligence and Lecture Notesin Bioinformatics) Preface vol 9204 pp 274ndash283 2015

[55] T W Chim S-M Yiu V O Li L C Hui and J ZhongldquoPRGA Privacy-Preserving Recording amp Gateway-AssistedAuthentication of Power Usage Information for Smart GridrdquoIEEE Transactions on Dependable and Secure Computing vol12 no 1 pp 85ndash97 2015

[56] X Li J Niu S Kumari J Liao W Liang and M K Khan ldquoAnew authentication protocol for healthcare applications usingwirelessmedical sensor networkswith user anonymityrdquo Securityand Communication Networks vol 9 no 15 pp 2643ndash26552016

[57] D He N Kumar and N Chilamkurti ldquoA secure temporal-credential-based mutual authentication and key agreementscheme with pseudo identity for wireless sensor networksrdquoInformation Sciences vol 321 Article ID 11403 pp 263ndash2772015

[58] S Shin H Yeh and K Kim ldquoAn efficient secure authenticationscheme with user anonymity for roaming user in ubiquitousnetworksrdquo Peer-to-Peer Networking and Applications vol 8 no4 pp 674ndash683 2015

[59] G Prosanta and T Hwang ldquoLightweight and energy-efficientmutual authentication and key agreement scheme with useranonymity for secure communication in global mobility net-worksrdquo IEEE Systems Journal vol PP no 99 2015

[60] M S Farash S A Chaudhry M Heydari S M Sajad SadoughS Kumari and M K Khan ldquoA lightweight anonymous authen-tication scheme for consumer roaming in ubiquitous networkswith provable securityrdquo International Journal of CommunicationSystems vol 30 no 4 Article ID e3019 2017

[61] C Lai R Lu D Zheng H Li and X Sherman ldquoGLARMgroup-based lightweight authentication scheme for resource-constrained machine to machine communicationsrdquo ComputerNetworks vol 99 pp 66ndash81 2016

[62] D Chen N Zhang and Z Qin ldquoS2M a lightweight acousticfingerprints based wireless device authentication protocolrdquoIEEE Internet of Things Journal vol 4 no 1 pp 88ndash100 2017

[63] J Shao X Lin R Lu and C Zuo ldquoA Threshold AnonymousAuthentication Protocol for VANETsrdquo IEEE Transactions onVehicular Technology vol 65 no 3 pp 1711ndash1720 2016


[64] C Lyu D Gu Y Zeng and P Mohapatra ldquoPBA Prediction-Based Authentication for Vehicle-to-Vehicle CommunicationsrdquoIEEETransactions onDependable and Secure Computing vol 13no 1 pp 71ndash83 2016

[65] L Zhang Q Wu J Domingo-Ferrer B Qin and C HuldquoDistributed Aggregate Privacy-Preserving Authentication inVANETsrdquo IEEE Transactions on Intelligent Transportation Sys-tems pp 1ndash11 2016

[66] S Dolev Ł Krzywiecki N Panwar and M Segal ldquoVehi-cle authentication via monolithically certified public key andattributesrdquoWireless Networks vol 22 no 3 pp 879ndash896 2016

[67] K Mahmood S Ashraf Chaudhry H Naqvi T Shon and HFarooq Ahmad ldquoA lightweight message authentication schemefor Smart Grid communications in power sectorrdquo ComputersElectrical Engineering vol 52 pp 114ndash124 2016

[68] S Kumari X Li F Wu A K Das H Arshad and M K KhanldquoA user friendly mutual authentication and key agreementscheme for wireless sensor networks using chaotic mapsrdquoFuture Generation Computer Systems vol 63 pp 56ndash75 2016

[69] Y Chung S Choi Y S Lee N Park andDWon ldquoAn enhancedlightweight anonymous authentication scheme for a scalablelocalization roaming service in wireless sensor networksrdquo Sen-sors vol 16 no 10 article no 1653 2016

[70] R Amin and G Biswas ldquoA secure light weight scheme foruser authentication and key agreement in multi-gateway basedwireless sensor networksrdquo Ad Hoc Networks vol 36 part 1 pp58ndash80 2016

[71] P Gope and T Hwang ldquoA realistic lightweight anonymousauthentication protocol for securing real-time application dataaccess in wireless sensor networksrdquo IEEE Transactions onIndustrial Electronics 2016

[72] A K Das ldquoA secure and robust temporal credential-basedthree-factor user authentication scheme for wireless sensornetworksrdquo Peer-to-Peer Networking and Applications vol 9 no1 pp 223ndash244 2016

[73] C-C Chang and H-D Le ldquoA Provably Secure Efficient andFlexible Authentication Scheme for Ad hoc Wireless SensorNetworksrdquo IEEE Transactions onWireless Communications vol15 no 1 pp 357ndash366 2016

[74] Q Jiang J Ma F Wei Y Tian J Shen and Y Yang ldquoAnuntraceable temporal-credential-based two-factor authentica-tion scheme using ECC for wireless sensor networksrdquo Journalof Network and Computer Applications vol 76 pp 37ndash48 2016

[75] M S Farash M Turkanovic S Kumari and M Holbl ldquoAnefficient user authentication and key agreement scheme forheterogeneous wireless sensor network tailored for the Internetof Things environmentrdquo Ad Hoc Networks vol 36 pp 152ndash1762016

[76] S Kumari A K Das MWazid et al ldquoOn the design of a secureuser authentication and key agreement scheme for wirelesssensor networksrdquo Concurrency Computation 2016

[77] Q Jiang N Kumar J Ma J Shen D He and N ChilamkurtildquoA privacy-aware two-factor authentication protocol basedon elliptic curve cryptography for wireless sensor networksrdquoInternational Journal of Network Management vol 27 no 3Article ID e1937 2017

[78] A Karkouch H Mousannif H Al Moatassime and T NoelldquoData quality in internet of things A state-of-the-art surveyrdquoJournal of Network and Computer Applications vol 73 pp 57ndash81 2016

[79] Q Yongrui Q Z Sheng N J G Falkner S Dustdar H Wangand A V Vasilakos ldquoWhen things matter a survey on data-centric internet of thingsrdquo Journal of Network and ComputerApplications vol 64 pp 137ndash153 2016

[80] N C Luong D T Hoang P Wang D Niyato D I Kimand Z Han ldquoData Collection and Wireless Communication inInternet of Things (IoT) Using Economic Analysis and PricingModels A Surveyrdquo IEEE Communications Surveys amp Tutorialsvol 18 no 4 pp 2546ndash2590 2016

[81] S Bandyopadhyay M Sengupta S Maiti and S Dutta ldquoAsurvey of middleware for internet of thingsrdquo in Recent Trendsin Wireless and Mobile Networks vol 162 of Communicationsin Computer and Information Science pp 288ndash296 SpringerBerlin Germany 2011

[82] M A Chaqfeh and N Mohamed ldquoChallenges in middlewaresolutions for the internet of thingsrdquo in Proceedings of the13th International Conference on Collaboration Technologies andSystems (CTS rsquo12) pp 21ndash26 Denver Colo USA May 2012

[83] T Teixeira S Hachem V Issarny and N Georgantas ldquoServiceoriented middleware for the internet of things A perspective(invited paper)rdquo Lecture Notes in Computer Science (includingsubseries Lecture Notes in Artificial Intelligence and Lecture Notesin Bioinformatics) Preface vol 6994 pp 220ndash229 2011

[84] M A Razzaque M Milojevic-Jevric A Palade and S ClarkeldquoMiddleware for Internet of things a surveyrdquo IEEE Internet ofThings Journal vol 3 no 1 pp 70ndash95 2016

[85] A Zanella N Bui A P Castellani L Vangelista and M ZorzildquoInternet of things for smart citiesrdquo IEEE Internet of ThingsJournal vol 1 no 1 pp 22ndash32 2014

[86] E Ahmed I Yaqoob A Gani M Imran and M GuizanildquoInternet-of-things-based smart environments State of theart taxonomy and open research challengesrdquo IEEE WirelessCommunications Magazine vol 23 no 5 pp 10ndash16 2016

[87] A Gluhak S Krco M Nati D Pfisterer N Mitton andT Razafindralambo ldquoA survey on facilities for experimentalinternet of things researchrdquo IEEE Communications Magazinevol 49 no 11 pp 58ndash67 2011

[88] L Mainetti L Patrono and A Vilei ldquoEvolution of wirelesssensor networks towards the Internet of Things a surveyrdquo inProceedings of the 19th International Conference on SoftwareTelecommunications and Computer Networks (SoftCOM rsquo11) pp16ndash21 September 2011

[89] R Roman C Alcaraz J Lopez and N Sklavos ldquoKey manage-ment systems for sensor networks in the context of the Internetof Thingsrdquo Computers Electrical Engineering vol 37 no 2 pp147ndash159 2011

[90] C C Aggarwal N Ashish and A Sheth ldquoThe Internetof Things A Survey from the Data-Centric Perspectiverdquo inManaging and Mining Sensor Data pp 383ndash428 Springer USBoston MA 2013

[91] N Bizanis and F A Kuipers ldquoSDN and virtualization solutionsfor the internet of things a surveyrdquo IEEEAccess vol 4 pp 5591ndash5606 2016

[92] P Rawat K D Singh and J M Bonnin ldquoCognitive radio forM2M and Internet of Things A surveyrdquo Computer Communi-cations vol 94 pp 1ndash29 2016

[93] D Bandyopadhyay and J Sen ldquoInternet of things applicationsand challenges in technology and standardizationrdquo WirelessPersonal Communications vol 58 no 1 pp 49ndash69 2011

[94] D Miorandi S Sicari F de Pellegrini and I Chlamtac ldquoInter-net of things vision applications and research challengesrdquo AdHoc Networks vol 10 no 7 pp 1497ndash1516 2012


[95] Z G Sheng S S Yang Y F Yu A V Vasilakos J A McCannand K K Leung ldquoA survey on the ietf protocol suite for theinternet of things standards challenges and opportunitiesrdquoIEEEWireless Communications Magazine vol 20 no 6 pp 91ndash98 2013

[96] I Ishaq D Carels G Teklemariam et al ldquoIETF standardizationin the field of the internet of things (IoT) a surveyrdquo Journal ofSensor and Actuator Networks vol 2 no 2 pp 235ndash287 2013

[97] M R Palattella N Accettura X Vilajosana et al ldquoStandardizedprotocol stack for the internet of (important) thingsrdquo IEEECommunications Surveys amp Tutorials vol 15 no 3 pp 1389ndash1406 2013

[98] C-W Tsai C-F Lai and A V Vasilakos ldquoFuture internet ofthings open issues and challengesrdquo Wireless Networks vol 20no 8 pp 2201ndash2217 2014

[99] M C Domingo ldquoAn overview of the internet of things forpeople with disabilitiesrdquo Journal of Network and ComputerApplications vol 35 no 2 pp 584ndash596 2012

[100] L D Xu W He and S Li ldquoInternet of things in industries Asurveyrdquo IEEE Transactions on Industrial Informatics vol 10 no4 pp 2233ndash2243 2014

[101] C Perera C H Liu S Jayawardena and M Chen ldquoA surveyon internet of things from industrial market perspectiverdquo IEEEAccess vol 2 pp 1660ndash1679 2014

[102] Z Bi L D Xu and C Wang ldquoInternet of things for enterprisesystems of modern manufacturingrdquo IEEE Transactions onIndustrial Informatics vol 10 no 2 pp 1537ndash1546 2014

[103] M R Abdmeziem D Tandjaoui and I Romdhani ldquoArchitect-ing the internet of things state of the artrdquo pp 55ndash75 2016

[104] D Zhang L T Yang and H Huang ldquoSearching in Internet ofThings Vision and challengesrdquo in Proceedings of the 9th IEEEInternational Symposium on Parallel and Distributed Processingwith Applications ISPA 2011 pp 201ndash206 kor May 2011

[105] H Suo J Wan C Zou and J Liu ldquoSecurity in the internet ofthings a reviewrdquo in Proceedings of the International Conferenceon Computer Science and Electronics Engineering (ICCSEE rsquo12)pp 648ndash651 Hangzhou China March 2012

[106] R Roman J Zhou and J Lopez ldquoOn the features and challengesof security and privacy in distributed internet of thingsrdquoComputer Networks vol 57 no 10 pp 2266ndash2279 2013

[107] Z Yan P Zhang and A V Vasilakos ldquoA survey on trustmanagement for Internet of Thingsrdquo Journal of Network andComputer Applications vol 42 pp 120ndash134 2014

[108] Q Jing A V Vasilakos J Wan J Lu and D Qiu ldquoSecurityof the internet of things perspectives and challengesrdquo WirelessNetworks vol 20 no 8 pp 2481ndash2501 2014

[109] S Chabridon R Laborde T Desprats A Oglaza P Marieand S M Marquez ldquoA survey on addressing privacy togetherwith quality of context for context management in the Inter-net of Thingsrdquo Annals of Telecommunications-Annales desTelecommunications vol 69 no 1-2 pp 47ndash62 2014

[110] J H Ziegeldorf O G Morchon and K Wehrle ldquoPrivacy inthe internet of things threats and challengesrdquo Security andCommunication Networks vol 7 no 12 pp 2728ndash2742 2014

[111] W Xie Y Tang S Chen Y Zhang and Y Gao ldquoSecurity ofWebof Things A Survey (Short Paper)rdquo in Advances in Informationand Computer Security vol 9836 of Lecture Notes in ComputerScience pp 61ndash70 Springer International Publishing Cham2016

[112] S L Keoh S S Kumar and H Tschofenig ldquoSecuring theinternet of things a standardization perspectiverdquo IEEE Internetof Things Journal vol 1 no 3 pp 265ndash275 2014

[113] S Sicari A Rizzardi L A Grieco and A Coen-PorisinildquoSecurity privacy and trust in Internet of Things the roadaheadrdquo Computer Networks vol 76 pp 146ndash164 2015

[114] J Granjal E Monteiro and J Sa Silva ldquoSecurity for the internetof things a survey of existing protocols and open researchissuesrdquo IEEE Communications Surveys amp Tutorials vol 17 no3 pp 1294ndash1312 2015

[115] A-R Sadeghi C Wachsmann and M Waidner ldquoSecurityand privacy challenges in industrial internet of thingsrdquo inProceedings of the 52nd ACMEDACIEEE Design AutomationConference (DAC rsquo15) pp 1ndash6 IEEE San Francisco Calif USAJune 2015

[116] K T Nguyen M Laurent and N Oualha ldquoSurvey on securecommunication protocols for the Internet of Thingsrdquo Ad HocNetworks vol 32 article no 1181 pp 17ndash31 2015

[117] J Singh T Pasquier J Bacon H Ko and D Eyers ldquoTwentySecurity Considerations for Cloud-Supported Internet ofThingsrdquo IEEE Internet of Things Journal vol 3 no 3 pp 269ndash284 2016

[118] S Li T Tryfonas and H Li ldquoThe Internet of Things a securitypoint of viewrdquo Internet Research vol 26 no 2 pp 337ndash359 2016

[119] D Airehrour J Gutierrez and S K Ray ldquoSecure routing forinternet of things A surveyrdquo Journal of Network and ComputerApplications vol 66 pp 198ndash213 2016

[120] X Jia Q Feng T Fan and Q Lei ldquoRFID technology andits applications in Internet of Things (IoT)rdquo in Proceedings ofthe 2012 2nd International Conference on Consumer ElectronicsCommunications and Networks CECNet 2012 pp 1282ndash1285chn April 2012

[121] D He and S Zeadally ldquoAn Analysis of RFID AuthenticationSchemes for Internet of Things in Healthcare EnvironmentUsing Elliptic Curve Cryptographyrdquo IEEE Internet of ThingsJournal vol 2 no 1 pp 72ndash83 2015

[122] L Atzori A Iera GMorabito andMNitti ldquoThe social internetof things (SIoT)mdashwhen social networks meet the internet ofthings concept architecture and network characterizationrdquoComputer Networks vol 56 no 16 pp 3594ndash3608 2012

[123] B Guo D Zhang ZWang Z Yu and X Zhou ldquoOpportunisticIoT exploring the harmonious interaction between humanand the internet of thingsrdquo Journal of Network and ComputerApplications vol 36 no 6 pp 1531ndash1539 2013

[124] A M Ortiz D Hussein S Park S N Han and N Crespi ldquoThecluster between internet of things and social networks Reviewand research challengesrdquo IEEE Internet of Things Journal vol 1no 3 pp 206ndash215 2014

[125] L Maglaras A Al-Bayatti Y He I Wagner and H JanickeldquoSocial Internet of Vehicles for Smart Citiesrdquo Journal of Sensorand Actuator Networks vol 5 no 1 p 3 2016

[126] H-D Ma ldquoInternet of things objectives and scientific chal-lengesrdquo Journal of Computer Science and Technology vol 26 no6 pp 919ndash924 2011

[127] F Bonomi R Milito J Zhu and S Addepalli ldquoFog computingand its role in the internet of thingsrdquo in Proceedings of the 1stACMMobile Cloud ComputingWorkshop MCC 2012 pp 13ndash15fin August 2012

[128] A Botta W De Donato V Persico and A Pescape ldquoOnthe integration of cloud computing and internet of thingsrdquoin Proceedings of the 2nd International Conference on FutureInternet ofThings and Cloud (FiCloud rsquo14) pp 23ndash30 BarcelonaSpain August 2014


[129] A Whitmore A Agarwal and L Da Xu ldquoThe internet ofthingsmdasha survey of topics and trendsrdquo Information SystemsFrontiers vol 17 no 2 pp 261ndash274 2015

[130] A Al-Fuqaha M Guizani M Mohammadi M Aledhari andM Ayyash ldquoInternet of things a survey on enabling tech-nologies protocols and applicationsrdquo IEEE CommunicationsSurveys amp Tutorials vol 17 no 4 pp 2347ndash2376 2015

[131] A Botta W de Donato V Persico and A Pescape ldquoIntegrationof cloud computing and internet of things a surveyrdquo FutureGeneration Computer Systems vol 56 pp 684ndash700 2016

[132] J Liu H Shen and X Zhang ldquoA survey ofmobile crowdsensingtechniques A critical component for the internet of thingsrdquo inProceedings of the 25th International Conference on ComputerCommunications and Networks ICCCN 2016 usa August 2016

[133] D Gil A Ferrandez H Mora-Mora and J Peral ldquoInternet ofthings a review of surveys based on context aware intelligentservicesrdquo Sensors vol 16 no 7 article 1069 2016

[134] M Dıaz C Martın and B Rubio ldquoState-of-the-art challengesand open issues in the integration of Internet of things andcloud computingrdquo Journal of Network and Computer Applica-tions vol 67 pp 99ndash117 2016

[135] C Tsai C Lai M Chiang and L T Yang ldquoData mining forinternet of things a surveyrdquo IEEE Communications Surveys ampTutorials vol 16 no 1 pp 77ndash97 2014

[136] F Chen P Deng J Wan D Zhang A V Vasilakos and XRong ldquoData mining for the internet of things Literature reviewand challengesrdquo International Journal of Distributed SensorNetworks vol 2015 Article ID 431047 2015

[137] H Zhu X Lin Y Zhang and R Lu ldquoDuth A user-friendlydual-factor authentication for Android smartphone devicesrdquoSecurity and Communication Networks vol 8 no 7 pp 1213ndash1222 2015

[138] D Li Z Aung J R Williams and A Sanchez ldquoEfficientauthentication scheme for data aggregation in smart grid withfault tolerance and fault diagnosisrdquo in Proceedings of the IEEEPES Innovative Smart Grid Technologies (ISGT rsquo12) pp 1ndash8IEEE January 2012

[139] H Nicanfar P Jokar and V C M Leung ldquoSmart gridauthentication and key management for unicast and multicastcommunicationsrdquo in Proceedings of the IEEE Power and EnergySocietyrsquosInnovative Smart Grid Technologies Asia 2011 Confer-enceISGT Asia 2011 aus November 2011

[140] T W Chim S M Yiu L C K Hui and V O K LildquoPASS Privacy-preserving authentication scheme for smartgrid networkrdquo in Proceedings of the 2011 IEEE 2nd InternationalConference on Smart Grid Communications SmartGridComm2011 pp 196ndash201 bel October 2011

[141] M M Fouda Z M Fadlullah N Kato R Lu and X ShenldquoTowards a light-weight message authentication mechanismtailored for Smart Grid communicationsrdquo in Proceedings of the2011 IEEEConference onComputer CommunicationsWorkshopsINFOCOMWKSHPS 2011 pp 1018ndash1023 chn April 2011

[142] HNicanfar P Jokar K Beznosov andVCM Leung ldquoEfficientauthentication and keymanagementmechanisms for smart gridcommunicationsrdquo IEEE Systems Journal vol 8 no 2 pp 629ndash640 2014

[143] M Jan P Nanda M Usman and X He ldquoPAWN A payload-based mutual authentication scheme for wireless sensor net-worksrdquo Concurrency Computation 2016

[144] J Srinivas S Mukhopadhyay and D Mishra ldquoSecure andefficient user authentication scheme for multi-gateway wirelesssensor networksrdquo Ad Hoc Networks vol 54 pp 147ndash169 2017

[145] X Sun XWu C Huang Z Xu and J Zhong ldquoModified accesspolynomial based self-healing key management schemes withbroadcast authentication and enhanced collusion resistance inwireless sensor networksrdquo Ad Hoc Networks vol 37 pp 324ndash336 2016

[146] F Wu L Xu S Kumari and X Li ldquoAn improved and provablysecure three-factor user authentication scheme for wirelesssensor networksrdquo Peer-to-Peer Networking and Applications pp1ndash20 2016

[147] A K Das S Kumari V Odelu X Li F Wu and XHuang ldquoProvably secure user authentication and key agree-ment scheme for wireless sensor networksrdquo Security and Com-munication Networks vol 9 no 16 pp 3670ndash3687 2016

[148] C-H Liu and Y-F Chung ldquoSecure user authentication schemefor wireless healthcare sensor networksrdquoComputersamp ElectricalEngineering 2016

[149] J Katz and Y Lindell Introduction to Modern CryptographyChapman amp HallCRC 2007

[150] J Katz and A Y Lindell ldquoAggregate Message AuthenticationCodesrdquo in Topics in Cryptology CT-RSA pp 155ndash169 SpringerBerlin Heidelberg Berlin Heidelberg 2008

[151] H Xiong Z Guan Z Chen and F Li ldquoAn efficient certificate-less aggregate signature with constant pairing computationsrdquoInformation Sciences vol 219 pp 225ndash235 2013

[152] E Barker L Chen A Roginsky and M Smid ldquoRecommenda-tion for Pair-Wise Key Establishment Schemes Using DiscreteLogarithm Cryptographyrdquo National Institute of Standards andTechnology NIST SP 800-56Ar2 2013

[153] F Hess ldquoEfficient identity based signature schemes based onpairingsrdquo in Selected Areas in Cryptography vol 2595 pp 310ndash324 Springer Berlin Germany 2003

[154] P Chown ldquoAdvanced Encryption Standard (AES) Ciphersuitesfor Transport Layer Security (TLS)rdquo RFC Editor RFC32682002

[155] J Y Hwang S Lee B-H Chung H S Cho and D NyangldquoGroup signatures with controllable linkability for dynamicmembershiprdquo Information Sciences vol 222 pp 761ndash778 2013

[156] T Schmidt M Waehlisch and S Krishnan ldquoBase Deploymentfor Multicast Listener Support in Proxy Mobile IPv6 (PMIPv6)Domainsrdquo RFC Editor RFC6224 2011

[157] R Blom ldquoAn Optimal Class of Symmetric Key GenerationSystemsrdquo in Advances in Cryptology pp 335ndash338 SpringerBerlin Heidelberg Berlin Heidelberg 1984

[158] T H Cormen C E Leiserson R Rivest and C Stein Introduc-tion to Algorithms The MIT Press 2009

[159] D Chaum and E van Heyst ldquoGroup Signaturesrdquo in Advancesin Cryptology mdash EUROCRYPT rsquo91 vol 547 of Lecture Notesin Computer Science pp 257ndash265 Springer Berlin HeidelbergBerlin Heidelberg 1991

[160] D Boneh X Boyen and H Shacham ldquoShort group signaturesrdquoin Advances in CryptologymdashCRYPTO 2004 vol 3152 of LectureNotes inComputer Science pp 41ndash55 Springer BerlinGermany2004

[161] R C Merkle R Charles et al ldquoSecrecy authentication andpublic key systemsrdquo

[162] A Perrig R Canetti D SongU C Berkeley D Fountain and IB M T J Watson ldquoEfficient and Secure Source AuthenticationforMulticastrdquo in Proceedings of the Internet Society Network andDistributed System Security Symposium pp 35ndash46 2001

[163] ldquoIEEE Std 16092-2013rdquo IEEE standard for wireless access invehicular environments - Security services for applications andmanagement messages


[164] E Kiltz and K Pietrzak ldquoLeakage resilient ElGamal encryp-tionrdquo in Advances in CryptologymdashASIACRYPT rsquo10 vol 6477 ofLectureNotes inComputer Science pp 595ndash612 Springer BerlinGermany 2010

[165] D Boneh andH Shacham ldquoGroup signatureswith verifier-localrevocationrdquo inProceedings of the the 11thACMconference p 168Washington DC USA October 2004

[166] D Bleichenbacher and AMay ldquoNew attacks on RSAwith smallsecret CRT-exponentsrdquo in Public key cryptography-PKC vol3958 pp 1ndash13 Springer Berlin 2006

[167] D Pointcheval and J Stern ldquoSecurity arguments for digitalsignatures and blind signaturesrdquo Journal of Cryptology vol 13no 3 pp 361ndash396 2000

[168] B Li Z Wang and D Huang ldquoAn Efficient and AnonymousAttribute-Based group setup schemerdquo in Proceedings of the 2013IEEE Global Communications Conference GLOBECOM 2013pp 861ndash866 usa December 2013

[169] H Krawczyk M Bellare and R Canetti ldquoRFC2104 - HMACKeyed-hashing for message authenticationrdquo Tech Rep 1997arXivarXiv10111669v3

[170] L Reyzin and N Reyzin ldquoBetter than BiBa Short One-TimeSignatures with Fast Signing and Verifyingrdquo in InformationSecurity and Privacy vol 2384 of Lecture Notes in ComputerScience pp 144ndash153 Springer Berlin Heidelberg Berlin Hei-delberg 2002

[171] R Rivest ldquoThe MD5 Message-Digest Algorithmrdquo RFC EditorRFC1321 1992

[172] D Boneh B Lynn and H Shacham ldquoShort signatures fromthe Weil pairingrdquo Journal of Cryptology The Journal of theInternational Association for Cryptologic Research vol 17 no 4pp 297ndash319 2004

[173] L Harn ldquoBatch verifyingmultiple RSA digital signaturesrdquo IEEEElectronics Letters vol 34 no 12 pp 1219-1220 1998

[174] D Boneh C Gentry B Lynn and H Shacham ldquoAggregate andverifiably encrypted signatures frombilinearmapsrdquo inAdvancesin cryptologymdashEUROCRYPT 2003 vol 2656 of Lecture Notes inComput Sci pp 416ndash432 Springer Berlin 2003

[175] J Jonsson and B Kaliski ldquoPublic-Key Cryptography Standards(PKCS) 1 RSA Cryptography Specifications Version 21rdquo RFCEditor RFC3447 2003

[176] P Jones ldquoUS secure hash algorithm 1 (SHA1) RFC 3174rdquo TechRep 2001 httprsynctoolsietforghtmlrfc3174

[177] S Turner and L Chen ldquoUpdated Security Considerations forthe MD5 Message-Digest and the HMAC-MD5 AlgorithmsrdquoRFC Editor RFC6151 2011

[178] D R Stinson Cryptography theory and practice CRC press2002

[179] H Nicanfar and V C M Leung ldquoEIBC Enhanced identity-based cryptography a conceptual designrdquo in Proceedings of the2012 6th IEEE International Systems Conference SysCon 2012pp 179ndash185 can March 2012

[180] D Boneh andM Franklin ldquoIdentity-based encryption from theWeil pairingrdquo in Advances in CryptologymdashCRYPTO 2001 vol2139 of Lecture Notes in Computer Science pp 213ndash229 2001

[181] P Paillier ldquoPublic-key cryptosystems based on compos-ite degree residuosity classesrdquo in Advances in CryptologymdashEUROCRYPT rsquo99 vol 1592 pp 223ndash238 Springer 1999

[182] A Kumar J JimXu and J Wang ldquoSpace-code bloom filter forefficient per-flow trafficmeasurementrdquo IEEE Journal on SelectedAreas in Communications vol 24 no 12 pp 2327ndash2339 2006

[183] J CMason andDCHandscombChebyshev Polynomials CRCPress Boca Raton Fla USA 2003

[184] S Han and E Chang ldquoChaotic map based key agreementwithout clock synchronization Chaosrdquo Solitonsamp Fractals vol39 no 3 pp 1283ndash1289 2009

[185] J Daemen and V Rijmen The Design of Rijndael AES-TheAdvanced Encryption Standard Springer Berlin Germany2002

[186] Y Dodis R Ostrovsky L Reyzin and A Smith ldquoFuzzyextractors how to generate strong keys from biometrics andother noisy datardquo SIAM Journal on Computing vol 38 no 1pp 97ndash139 2008

[187] A T B Jin D N C Ling and A Goh ldquoBiohashing Two factorauthentication featuring fingerprint data and tokenised randomnumberrdquo Pattern Recognition vol 37 no 11 pp 2245ndash22552004

[188] R Dutta S Mukhopadhyay and T Dowling ldquoEnhanced AccessPolynomial Based Self-healing Key Distributionrdquo in Securityin Emerging Wireless Communication and Networking Systemsvol 42 of Lecture Notes of the Institute for Computer SciencesSocial Informatics and Telecommunications Engineering pp 13ndash24 Springer Berlin Heidelberg Berlin Heidelberg 2010

[189] D Hankerson S Vanstone and A J Menezes Guide to EllipticCurve Cryptography Springer New York NY USA 2004

[190] Q Jiang J Ma X Lu and Y Tian ldquoAn efficient two-factor userauthentication scheme with unlinkability for wireless sensornetworksrdquo Peer-to-Peer Networking and Applications vol 8 no6 pp 1070ndash1081 2015

[191] B Blanchet V Cheval X Allamigeon and B Smyth ProverifCryptographic protocol verifier in the formal model 2010

[192] M Abadi and A D Gordon ldquoA calculus for cryptographicprotocolsrdquo in Proceedings of the the 4th ACM conference pp 36ndash47 Zurich Switzerland April 1997

[193] ldquoNXP ATOP datasheetrdquo httpwwwnxpcomdocumentsleaflet939775016910pdf

[194] ldquoAVISPA-Automated Validation of Internet Security Protocolsrdquohttpwwwavispa-projectorg

[195] M Burrows M Abadi and R Needham ldquoLogic of authentica-tionrdquo ACM Transactions on Computer Systems vol 8 no 1 pp18ndash36 1990

[196] D Dolev and A C Yao ldquoOn the security of public keyprotocolsrdquo Institute of Electrical and Electronics Engineers Trans-actions on Information Theory vol 29 no 2 pp 198ndash208 1983

[197] A K Das A K Sutrala S Kumari V Odelu M Wazid and XLi ldquoAn efficient multi-gateway-based three-factor user authen-tication and key agreement scheme in hierarchical wirelesssensor networksrdquo Security and Communication Networks vol9 no 13 pp 2070ndash2092 2016

[198] G Chandrasekaran J-A Francisco V Ganapathy M GruteserandW Trappe ldquoDetecting identity spoofs in IEEE 80211e wire-less networksrdquo in Proceedings of the IEEE Global Telecommuni-cations Conference (GLOBECOM rsquo09) pp 1ndash6 IEEE December2009

[199] N Patwari and S K Kasera ldquoRobust location distinctionusing temporal link signaturesrdquo in Proceedings of the the 13thannual ACM international conference p 111 Montreal QuebecCanada September 2007

[200] L Xiao L Greenstein N Mandayam and W Trappe ldquoAphysical-layer technique to enhance authentication for mobileterminalsrdquo in Proceedings of the IEEE International Conferenceon Communications ICC 2008 pp 1520ndash1524 chn May 2008


[201] J Xiong andK Jamieson ldquoSecureArray improvingwifi securitywith fine-grained physical-layer information inrdquo in Proceedingsof the 19th annual international conference on Mobile computingnetworking - MobiCom 13 pp 441-10 New York New YorkUSA 2013

[202] C Zhang R Lu P-H Ho and A Chen ldquoA location privacypreserving authentication scheme in vehicular networksrdquo inProceedings of the IEEEWireless Communications and Network-ing Conference WCNC 2008 pp 2543ndash2548 usa April 2008

[203] I standard 80216m 2011 Air interface for broadband wirelessaccess systems - Amendment 3 advanced air interface

[204] C-M Huang and J-W Li ldquoA cluster-chain-based contexttransfer mechanism for fast basic service set transition in thecentralized wireless LAN architecturerdquo Wireless Communica-tions and Mobile Computing vol 9 no 10 pp 1387ndash1401 2009

[205] J Jeong Y C Min and H Choo ldquoIntegrated OTP-based userauthentication scheme using smart cards in home networksrdquo inProceedings of the 41st Annual Hawaii International Conferenceon System Sciences 2008 HICSS usa January 2008

[206] R Baldessari W Zhang A Festag and L Le ldquoA MANET-centric Solution for the Application of NEMO in VANETUsingGeographic Routingrdquo in Proceedings of the 4th InternationalConference on Testbeds and research infrastructures for thedevelopment of networks amp communities p 12 ICST (Institutefor Computer Sciences Social-Informatics and Telecommuni-cations Engineering) 2008

[207] ldquoISOIEC is 9798-3 Entity authentication mechanisms part 3Entity authentication using asymmetric techniquesrdquo

[208] H Krawczyk ldquoSIGMA The SIGn-and-MAc Approach toAuthenticated Diffie-Hellman and Its Use in the IKE Protocolsrdquoin Proceedings of the Annual International Cryptology Confer-ence vol 2729 pp 400ndash425

[209] Q Wang H Khurana Y Huang and K Nahrstedt ldquoTimevalid one-time signature for time-criticalmulticast data authen-ticationrdquo in Proceedings of the 28th Conference on ComputerCommunications IEEE INFOCOM 2009 pp 1233ndash1241 braApril 2009

[210] H Gharavi and B Hu ldquoMultigate communication network forsmart gridrdquoProceedings of the IEEE vol 99 no 6 pp 1028ndash10452011

[211] W Shi and P Gong ldquoA new user authentication protocol forwireless sensor networks using elliptic curves cryptographyrdquoInternational Journal of Distributed Sensor Networks vol 2013Article ID 730831 2013

[212] E Borgia ldquoThe internet of things vision key features applica-tions and open issuesrdquo Computer Communications vol 54 pp1ndash31 2014

[213] S M Riazul Islam D Kwak M Humaun Kabir M Hossainand K-S Kwak ldquoThe internet of things for health care acomprehensive surveyrdquo IEEE Access vol 3 pp 678ndash708 2015

[214] Y YIN Y Zeng X Chen and Y Fan ldquoThe internet of thingsin healthcare An overviewrdquo Journal of Industrial InformationIntegration vol 1 pp 3ndash13 2016

[215] M A Ferrag N Chekkai and M Nafa ldquoSecuring EmbeddedSystems Cyberattacks Countermeasures and Challengesrdquo inSecuring Cyber-Physical Systems pp 279ndash304 CRC Press 2015

[216] M A Ferrag M Nafa and S Ghanemi ldquoSecurity and privacyin mobile Ad Hoc social networksrdquo Security Privacy Trust andResource Management in Mobile and Wireless Communicationspp 222ndash243 2013

[217] M Ferrag M Nafa and S Ghanemi ldquoSecurity and Privacy forRouting Protocols in Mobile Ad Hoc Networksrdquo in Security forMultihop Wireless Networks pp 19ndash42 CRC Press 2014

[218] Security Solutions and Applied Cryptography in Smart GridCommunicationsM A Ferrag andAAhmim Eds IGIGlobal2017

[219] M A Ferrag L A Maglaras H Janicke and J Jiang ldquoA Surveyon Privacy-preserving Schemes for Smart Grid Communica-tionsrdquo httparxivorgabs161107722

[220] M A Ferrag L Maglaras and A Ahmim ldquoPrivacy-preservingschemes for Ad Hoc Social Networks A surveyrdquo IEEE Commu-nications Surveys amp Tutorials pp 1-1

[221] J Arkko V Devarapalli and F Dupont ldquoUsing IPsec to ProtectMobile IPv6 Signaling Between Mobile Nodes and HomeAgentsrdquo RFC Editor RFC3776 2004

[222] D Coppersmith ldquoData Encryption Standard (DES) and itsstrength against attacksrdquo IBM Journal of Research and Develop-ment vol 38 no 3 pp 243ndash250 1994

[223] C P Schnorr and M Jakobsson ldquoSecurity of signed ElGamalencryptionrdquo in Advances in cryptologymdashASIACRYPT 2000 vol1976 of Lecture Notes in Computer Science pp 73ndash89 SpringerBerlin Germany 2000

[224] S Gundavelli K Leung V Devarapalli K Chowdhury and BPatil ldquoProxy Mobile IPv6rdquo RFC Editor RFC5213 2008

[225] I Rivin ldquoSymmetrized Chebyshev polynomialsrdquo Proceedings ofthe American Mathematical Society vol 133 no 5 pp 1299ndash1305 2005

[226] H-Y Chien J-K Jan and Y-M Tseng ldquoAn Efficient andPractical Solution to Remote Authentication Smart CardrdquoComputers amp Security vol 21 no 4 pp 372ndash375 2002

[227] M H Manshaei Q Zhu T Alpcan T Basar and J-P HubauxldquoGame theory meets network security and privacyrdquo ACMComputing Surveys vol 45 no 3 article 25 2013

[228] G T V1250 3GPP System Architecture Evolution (SAE) Secu-rity architecture

[229] A Esfahani G Mantas R Matischek et al ldquoA LightweightAuthentication Mechanism for M2M Communications inIndustrial IoT Environmentrdquo IEEE Internet of Things Journalpp 1-1

[230] C Zhao L Huang Y Zhao and X Du ldquoSecure machine-typecommunications toward LTE heterogeneous networksrdquo IEEEWireless Communications Magazine vol 24 no 1 pp 82ndash872017

[231] Y Qiu and M Ma ldquoA mutual authentication and key estab-lishment scheme for M2M communication in 6LoWPAN net-worksrdquo IEEE Transactions on Industrial Informatics vol PP no99 2016

[232] R Amin N Kumar G P Biswas R Iqbal and V Chang ldquoAlight weight authentication protocol for IoT-enabled devices indistributed Cloud Computing environmentrdquo Future GenerationComputer Systems 2016

[233] S H Islam P Vijayakumar M Z Bhuiyan R Amin V RM and B Balusamy ldquoA Provably Secure Three-factor SessionInitiation Protocol for Multimedia Big Data CommunicationsrdquoIEEE Internet of Things Journal pp 1-1

[234] R Amin R Sherratt D Giri S Islam andM Khan ldquoA softwareagent enabled biometric security algorithm for secure file accessin consumer storage devicesrdquo IEEE Transactions on ConsumerElectronics vol 63 no 1 pp 53ndash61 2017

[235] M A Ferrag and A Ahmim ldquoESSPR an efficient securerouting scheme based on searchable encryption with vehicle


proxy re-encryption for vehicular peer-to-peer social networkrdquoTelecommunication Systems pp 1ndash23 2017

[236] N Saxena B J Choi and R Lu ldquoAuthentication andAuthoriza-tion Scheme for Various User Roles andDevices in Smart GridrdquoIEEE Transactions on Information Forensics and Security vol 11no 5 pp 907ndash921 2016

[237] Introduction to NISTIR 7628 Guidelines for Smart Grid CyberSecurity National Institute of Standards and Technologyhttpswwwnistgovsitesdefaultfilesdocumentssmartgridnistir-7628 totalpdf

[238] J Granjal E Monteiro and J S Silva ldquoSecurity in the integra-tion of low-power Wireless Sensor Networks with the InternetA surveyrdquo Ad Hoc Networks vol 24 pp 264ndash287 2015

[239] S Kumari M K Khan and M Atiquzzaman ldquoUser authenti-cation schemes for wireless sensor networks A reviewrdquo Ad HocNetworks vol 27 pp 159ndash194 2015

[240] K Grover and A Lim ldquoA survey of broadcast authenticationschemes for wireless networksrdquo Ad Hoc Networks vol 24 pp288ndash316 2015

[241] F Ishmanov A S Malik S W Kim and B Begalov ldquoTrustmanagement system in wireless sensor networks design con-siderations and research challengesrdquo Transactions on EmergingTelecommunications Technologies vol 26 no 2 pp 107ndash1302015

[242] C-Y Chen and H-C Chao ldquoA survey of key distributionin wireless sensor networksrdquo Security and CommunicationNetworks vol 7 no 12 pp 2495ndash2508 2014

[243] M A Simplicio Jr B T De Oliveira C B Margi P S L MBarreto T C M B Carvalho and M Naslund ldquoSurvey andcomparison of message authentication solutions on wirelesssensor networksrdquo Ad Hoc Networks vol 11 no 3 pp 1221ndash12362013

[244] M A FerragMNafa and S Ghanemi ldquoEPSA An efficient andprivacy-preserving scheme against wormhole attack on reactiverouting for mobile ad hoc social networksrdquo International Jour-nal of Security and Networks vol 11 no 3 pp 107ndash125 2016

[245] W R Heinzelman A Chandrakasan and H Balakrish-nan ldquoEnergy-efficient communication protocol for wirelessmicrosensor networksrdquo in Proceedings of the 33rd AnnualHawaii International Conference on System Siences (HICSS rsquo00)vol 2 IEEE January 2000

[246] L BOliveira A FerreiraMAVilaca et al ldquoSecLEACH-on thesecurity of clustered sensor networksrdquo Signal Processing vol 87no 12 pp 2882ndash2895 2007

[247] A K Das ldquoA Secure and Efficient User Anonymity-PreservingThree-Factor Authentication Protocol for Large-Scale Dis-tributed Wireless Sensor NetworksrdquoWireless Personal Commu-nications vol 82 no 3 pp 1377ndash1404 2015

[248] S G Yoo K Y Park and J Kim ldquoA security-performance-balanced user authentication scheme for wireless sensor net-worksrdquo International Journal of Distributed Sensor Networksvol 2012 Article ID 382810 11 pages 2012

[249] D-Z Sun J-X Li Z-Y Feng Z-F Cao and G-Q Xu ldquoON thesecurity and improvement of a two-factor user authenticationscheme in wireless sensor networksrdquo Personal and UbiquitousComputing vol 17 no 5 pp 895ndash905 2013

[250] J Nam M Kim J Paik Y Lee and D Won ldquoA provably-secure ECC-based authentication scheme for wireless sensornetworksrdquo Sensors vol 14 no 11 pp 21023ndash21044 2014

[251] A Das ldquoA secure and effective biometric-based user authen-tication scheme for wireless sensor networks using smart card

and fuzzy extractorrdquo International Journal of CommunicationSystems vol 30 no 1 Article ID e2933 2017

[252] K H M Wong Z Yuan C Jiannong and W ShengweildquoA dynamic user authentication scheme for wireless sensornetworksrdquo in Proceedings of the IEEE International Conferenceon Sensor Networks Ubiquitous and Trustworthy Computingvol 1 pp 244ndash251 Taichung Taiwan June 2006

[253] M L Das ldquoTwo-factor user authentication in wireless sensornetworksrdquo IEEE Transactions on Wireless Communications vol8 no 3 pp 1086ndash1090 2009

[254] P Gope J Lee and T Q S Quek ldquoResilience of DoS Attacksin Designing Anonymous User Authentication Protocol forWireless Sensor Networksrdquo IEEE Sensors Journal vol 17 no 2pp 498ndash503 2017

[255] C Benzaid K Lounis A Al-Nemrat N Badache and MAlazab ldquoFast authentication in wireless sensor networksrdquoFuture Generation Computer Systems vol 55 pp 362ndash375 2016

[256] X Cao W Kou L Dang and B Zhao ldquoIMBAS Identity-based multi-user broadcast authentication in wireless sensornetworksrdquo Computer Communications vol 31 no 4 pp 659ndash667 2008

[257] X Fan and G Gong ldquoAccelerating signature-based broadcastauthentication for wireless sensor networksrdquo Ad Hoc Networksvol 10 no 4 pp 723ndash736 2012

[258] S Kumari M Karuppiah X Li F Wu A K Das and VOdelu ldquoAn enhanced and secure trust-extended authenticationmechanism for vehicular ad-hoc networksrdquo Security and Com-munication Networks vol 9 no 17 pp 4255ndash4271 2016

[259] M Nitti R Girau A Floris and L Atzori ldquoOn adding thesocial dimension to the Internet of Vehicles Friendship andmiddlewarerdquo in Proceedings of the 2014 IEEE InternationalBlack Sea Conference on Communications and NetworkingBlackSeaCom 2014 pp 134ndash138 mda May 2014

[260] T H Luan R Lu X Shen and F Bai ldquoSocial on the roadenabling secure and efficient social networking on highwaysrdquoIEEEWireless Communications Magazine vol 22 no 1 pp 44ndash51 2015

[261] A Gantman andDM Jacobson Secure software authenticationand verification 2015

[262] M M Haghighi and M S Zamani ldquoSoft IP protection Anactive approach based on hardware authenticationrdquo in Proceed-ings of the 24th Iranian Conference on Electrical EngineeringICEE 2016 pp 1049ndash1054 irn May 2016

[263] H U D Z C L I U Peng ldquoRFID Middleware AuthenticationProtocol Design Based on Symmetrical Cryptographic Algo-rithmrdquo Computer amp Digital Engineering vol 3 p 36 2013

[264] S Raza L Wallgren and T Voigt ldquoSVELTE Real-time intru-sion detection in the Internet of Thingsrdquo Ad Hoc Networks vol11 no 8 pp 2661ndash2674 2013

[265] D Shah and V Haradi ldquoIoT Based Biometrics Implementationon Raspberry Pirdquo in Proceedings of the 7th International Confer-ence on Communication Computing and Virtualization ICCCV2016 pp 328ndash336 ind February 2016

[266] N Karimian P A Wortman and F Tehranipoor ldquoEvolvingauthentication design considerations for the Internet of biomet-ric things (IoBT)rdquo in Proceedings of the 2016 International Con-ference on HardwareSoftware Codesign and System SynthesisCODES+ISSS 2016 usa October 2016

[267] D JWu A Taly A Shankar andD Boneh ldquoPrivacy Discoveryand Authentication for the Internet of Thingsrdquo in ComputerSecurity ndash ESORICS 2016 vol 9879 of Lecture Notes in Computer


Science pp 301ndash319 Springer International Publishing Cham2016

[268] P Schulz M Matthe H Klessig et al ldquoLatency Critical IoTApplications in 5G Perspective on theDesign of Radio Interfaceand Network Architecturerdquo IEEE Communications Magazinevol 55 no 2 pp 70ndash78 2017

[269] M A Ferrag L Maglaras A Argyriou D Kosmanos andH Janicke Security for 4G and 5G Cellular Networks A Sur-vey of Existing Authentication and Privacy-preserving Schemeshttparxivorgabs170804027

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Active and Passive Electronic Components

Control Scienceand Engineering

Journal of


International Journal of

RotatingMachinery


Hindawi Publishing Corporation httpwwwhindawicom

Journal of

Volume 201

Submit your manuscripts athttpswwwhindawicom

VLSI Design



Shock and Vibration


Civil EngineeringAdvances in

Acoustics and VibrationAdvances in



Electrical and Computer Engineering

Journal of

Advances inOptoElectronics


Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of


Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014


Chemical EngineeringInternational Journal of Antennas and

Propagation




Navigation and Observation



DistributedSensor Networks



Data owData ow

Pow ow

Smart

E-Vehicle

Hotspot Service

Charging station

Control center (CC)

Control center

Control ow

Vehicle to grid (V2G) networkVehicle to grid

Notations

(V2G) network

Generation

Transmission

Distribution

Customers

Machine

Machine

SCADA system

Socialspot

User

User to user communication

User to socialspot communication

Gateway

Gateway

InternetHttpwww



Machine



middot middot middot

X

X

Figure 1 Internet of Things (IoT) in four environments including (1) Internet of Vehicles (IoV) (2) Internet of Energy (IoE) (3) Internetof Sensors (IoS) and (4) Machine to Machine Communications (M2M)

IEEE 802154 based protocols [12] The list of acronyms usedin this paper is listed in Acronyms Section

The vision of the IoT will advance based on many newfeatures and will cope with new challenges as shown inFigure 2 including cloud computing M2M IoS IoE IoVsocial networks software defined optical networks (SDONs)and fifth generation (5G) cellular networks The IoT datawhich will be produced from billions of interactions betweendevices and people is going to be not only massive but alsocomplex and it will suffer from many security and privacyproblems especially regarding the authentication amongdevices To resolve these security issues researchers in thefield of computer security have developed many authentica-tion protocols applied in the context of the IoT The aim ofthe current survey paper is to provide a comprehensive and

systematic review of recent studies on published authentica-tion protocols for the IoT in four environments includingM2M IoV IoE and IoS More precisely more than fortyauthentication protocols are selected and examined in detailThe original set of papers was formed from the searchers runon SCOPUS and Web of Science from the period between2010 and 2016The search started on 15102016 and continueduntil the submission date of this paper See Table 1 for abreakdown of publication dates The main contributions ofthis paper are as follows

(i) Previous survey articles published in recent years thatdeal with the IoT are briefly presented

(ii) Authentication protocols in M2M IoV IoE andIoS that were evaluated under thirty-five attacks are


Internet today


Cloud computing





Social networks



















[6 81ndash84]

[6 85 86]

[87]

[7 80 88ndash92]

[93ndash98]

[99ndash103]

[104]

[15 16 89 90 94 105ndash119]

[120 121]

[122ndash125]

[5 6 90 93 94 99 126ndash134]

[135 136]

[100]

















3 Threat Models













privacy





















Our work 0
























































False BTS

False MS

False MS

Legitimate MS

Legitimate BTS

Legitimate Network
























False MS

－３1 －３2

－３3

I am －３1

I am－３

1




False MS

－３1 －３2

－３3

I am －３ 1

I am －３1


－３ 1rsquos

IP addr




119886 1198632 = V119887 1198633 = 119872 sdot 11990811988611199081198872) where 119886 119887 isin 119885

lowast119901 are


1199091 sdot 1198631199102 )minus1















False MS


D3



False MSMS





False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation










Internet today


Cloud computing





Social networks



















[6 81ndash84]

[6 85 86]

[87]

[7 80 88ndash92]

[93ndash98]

[99ndash103]

[104]

[15 16 89 90 94 105ndash119]

[120 121]

[122ndash125]

[5 6 90 93 94 99 126ndash134]

[135 136]

[100]

















3 Threat Models













privacy





















Our work 0
























































False BTS

False MS

False MS

Legitimate MS

Legitimate BTS

Legitimate Network
























False MS

－３1 －３2

－３3

I am －３1

I am－３

1




False MS

－３1 －３2

－３3

I am －３ 1

I am －３1


－３ 1rsquos

IP addr




119886 1198632 = V119887 1198633 = 119872 sdot 11990811988611199081198872) where 119886 119887 isin 119885

lowast119901 are


1199091 sdot 1198631199102 )minus1















False MS


D3



False MSMS





False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation












[6 81ndash84]

[6 85 86]

[87]

[7 80 88ndash92]

[93ndash98]

[99ndash103]

[104]

[15 16 89 90 94 105ndash119]

[120 121]

[122ndash125]

[5 6 90 93 94 99 126ndash134]

[135 136]

[100]

















3 Threat Models













privacy





















Our work 0
























































False BTS

False MS

False MS

Legitimate MS

Legitimate BTS

Legitimate Network
























False MS

－３1 －３2

－３3

I am －３1

I am－３

1




False MS

－３1 －３2

－３3

I am －３ 1

I am －３1


－３ 1rsquos

IP addr




119886 1198632 = V119887 1198633 = 119872 sdot 11990811988611199081198872) where 119886 119887 isin 119885

lowast119901 are


1199091 sdot 1198631199102 )minus1















False MS


D3



False MSMS





False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation




















3 Threat Models













privacy





















Our work 0
























































False BTS

False MS

False MS

Legitimate MS

Legitimate BTS

Legitimate Network
























False MS

－３1 －３2

－３3

I am －３1

I am－３

1




False MS

－３1 －３2

－３3

I am －３ 1

I am －３1


－３ 1rsquos

IP addr




119886 1198632 = V119887 1198633 = 119872 sdot 11990811988611199081198872) where 119886 119887 isin 119885

lowast119901 are


1199091 sdot 1198631199102 )minus1















False MS


D3



False MSMS





False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation
















privacy





















Our work 0
























































False BTS

False MS

False MS

Legitimate MS

Legitimate BTS

Legitimate Network
























False MS

－３1 －３2

－３3

I am －３1

I am－３

1




False MS

－３1 －３2

－３3

I am －３ 1

I am －３1


－３ 1rsquos

IP addr




119886 1198632 = V119887 1198633 = 119872 sdot 11990811988611199081198872) where 119886 119887 isin 119885

lowast119901 are


1199091 sdot 1198631199102 )minus1















False MS


D3



False MSMS





False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation






























































False BTS

False MS

False MS

Legitimate MS

Legitimate BTS

Legitimate Network
























False MS

－３1 －３2

－３3

I am －３1

I am－３

1




False MS

－３1 －３2

－３3

I am －３ 1

I am －３1


－３ 1rsquos

IP addr




119886 1198632 = V119887 1198633 = 119872 sdot 11990811988611199081198872) where 119886 119887 isin 119885

lowast119901 are


1199091 sdot 1198631199102 )minus1















False MS


D3



False MSMS





False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation





















































False BTS

False MS

False MS

Legitimate MS

Legitimate BTS

Legitimate Network
























False MS

－３1 －３2

－３3

I am －３1

I am－３

1




False MS

－３1 －３2

－３3

I am －３ 1

I am －３1


－３ 1rsquos

IP addr




119886 1198632 = V119887 1198633 = 119872 sdot 11990811988611199081198872) where 119886 119887 isin 119885

lowast119901 are


1199091 sdot 1198631199102 )minus1















False MS


D3



False MSMS





False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation














































False BTS

False MS

False MS

Legitimate MS

Legitimate BTS

Legitimate Network
























False MS

－３1 －３2

－３3

I am －３1

I am－３

1




False MS

－３1 －３2

－３3

I am －３ 1

I am －３1


－３ 1rsquos

IP addr




119886 1198632 = V119887 1198633 = 119872 sdot 11990811988611199081198872) where 119886 119887 isin 119885

lowast119901 are


1199091 sdot 1198631199102 )minus1















False MS


D3



False MSMS





False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation


































False BTS

False MS

False MS

Legitimate MS

Legitimate BTS

Legitimate Network
























False MS

－３1 －３2

－３3

I am －３1

I am－３

1




False MS

－３1 －３2

－３3

I am －３ 1

I am －３1


－３ 1rsquos

IP addr




119886 1198632 = V119887 1198633 = 119872 sdot 11990811988611199081198872) where 119886 119887 isin 119885

lowast119901 are


1199091 sdot 1198631199102 )minus1















False MS


D3



False MSMS





False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation























False BTS

False MS

False MS

Legitimate MS

Legitimate BTS

Legitimate Network
























False MS

－３1 －３2

－３3

I am －３1

I am－３

1




False MS

－３1 －３2

－３3

I am －３ 1

I am －３1


－３ 1rsquos

IP addr




119886 1198632 = V119887 1198633 = 119872 sdot 11990811988611199081198872) where 119886 119887 isin 119885

lowast119901 are


1199091 sdot 1198631199102 )minus1















False MS


D3



False MSMS





False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation




























False MS

－３1 －３2

－３3

I am －３1

I am－３

1




False MS

－３1 －３2

－３3

I am －３ 1

I am －３1


－３ 1rsquos

IP addr




119886 1198632 = V119887 1198633 = 119872 sdot 11990811988611199081198872) where 119886 119887 isin 119885

lowast119901 are


1199091 sdot 1198631199102 )minus1















False MS


D3



False MSMS





False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation





















False MS


D3



False MSMS





False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation










False MS

False MS


False MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

Legitimate MS

False MS

False MS

Attack edges




10158401198942 119904

1015840119896)) over message 119898 the



























TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation
































TESLA scheme [162]











HORS scheme [170]















Bloom filter [182]

Commitment scheme










Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation

















Biometric

Password

Smart card



Key agreement

Biohashing [187]




M2M IoV IoE IoS




Asymmetric-


Hybrid protocols



and so on

and so on

and so on












BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation
















BAN-logic


Gameeory


Automated

Automated

reasoning(ProVerif)

Validation(AVISPA)

















Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation














Shao et al (2016) [63]









authentication































Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation










Table 16 Continued








Das et al (2016) [147]








model



(iii) Anonymity











Maps



transmission


attacks





network model

(iv) and so on

(v) and so on

attack and so on

(iv) Untraceability










Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation












Lai et al(2016) [61]









Lai et al(2014) [46]





Lai et al(2013) [38]






Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation










Table 17 Continued


Fu et al(2012) [34]





Sun et al(2015) [53]





Lai et al(2014) [47]












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation












authentication



RFID authentication





































Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation

























Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation

















Shao et al(2016) [63]





Lyu et al (2016)[64]











Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation










Table 18 Continued
























Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation












Li and Cao(2011) [28]





Li et al (2014)[49]





Li et al (2012)[138]










Chim et al(2011) [140]





Fouda et al(2011) [141]






Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation










Table 19 Continued







Chim et al(2015) [55]











































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation






































Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation










Table 20 Continued












Sun et al(2016) [145]






















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation



















6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation











6 Open Issues
















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation















7 Conclusion



Acronyms








References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation












References

























































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation
































































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation

































































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation

































































































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation






























































































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation


























































































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation




















































































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation
















































RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation













RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation









RoboticsJournal of





Journal of



RotatingMachinery



Journal of

Volume 201


VLSI Design



Shock and Vibration







Journal of



Volume 2014


SensorsJournal of





Propagation









Documents

Authentication Protocols for Internet of Things: A ...downloads.hindawi.com/journals/scn/2017/6562953.pdf · Internet will consist of over 50 billion connected things, including sensors,