A Secure Framework for Flying Ad-hoc Networks

A Proposal

For

Doctor of Philosophy

Submitted By

Kuldeep Singh

(Registration No. 901403006)

Supervisor

Dr. Anil Kumar Verma

Associate Professor, CSED, Thapar University, Patiala, Punjab

COMPUTER SCIENCE AND ENGINEERING DEPARTMENT

THAPAR UNIVERSITY

PATIALA – 147004

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TABLE OF CONTENTS

Table of Content [i]

List of Figures [ii]

List of Tables [ii]

List of Abbreviations

1. Introduction

1.1 Wireless Network 1

1.2 Classification of Wireless Network 2

1.3 Infrastructure Based Network 2

1.4 Infrastructure Less Network 3

1.5 Wireless Sensor Network 3

1.6 Wireless Mesh Network 4

1.7 Mobile Ad-hoc Network 4

1.8 Vehicular Ad-hoc Network 5

1.9 Flying Ad-hoc Network 6

1.10 Comparison among MANET, VANET and FANET 8

2. Literature Survey

2.1 Literature Survey 9

3. Research Gaps

3.1 Research Gaps 18

4. Problem Statement

4.1 Problem Statement 20

4.2 Objectives 20

4.3 Methodology 20

4.4 Work Plan 21

References 22

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LIST OF FIGURES

Figure no. Name of Figure Page no.

Figure 1 Classification of Wireless Network 2

Figure 2 Infrastructure Based Network 2

Figure 3 Infrastructure- Less Network 3

Figure 4 Mobile Ad-hoc Network 4

Figure 5 Vehicular Ad-hoc Network 6

Figure 6 Flying Ad-hoc Network 7

LIST OF TABLES

Table no. Name of Table Page no.

Table 1 Common Attacks on MANET 5

Table 2 Comparison of different Ad-hoc Networks 8

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LIST OF ABERIVATIONS

AGPS Advance Global Positioning System

AES Advanced Encryption Standard

AODV Ad-hoc On-Demand Distance Vector

DES Data Encryption Standard

DoS Denial of Service

DOLSR Directional Optimized Link State Routing

DSDV Destination Sequenced Distance Vector Routing

DSR Dynamic Source Routing

ETX Expected Transmission Count

FANET Flying Ad-hoc Network

GPS Global Positioning System

IDS Intrusion Detection System

IEEE Institute of Electrical and Electronics Engineers

MANET Mobile Ad-hoc Network

MAV Micro Air Vehicle

MIMA Man In the Middle Attack

MN Mobile Node

MPR Multi Point Relay

NS Network Simulator

OLSR Optimized Link State Routing

UAV Unmanned Air Vehicle

VANET Vehicular Adhoc Network

WSN Wireless Sensor Network

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1. Introduction

1.1 Wireless Network

Wireless network is a type of network which does not require wires for establishing a connection

between computer systems or network nodes for data transfer. Wireless Networks are based on

the technology that uses the standard protocols for communication without physical cable

connections. Wireless networks works on IEEE standard 802.11. Multiple stations communicate

through radio waves that broadcast messages in either 2.4 GHz or 5 GHz band.

Wireless standard 802.11 first came up with sub-standard 802.11b that operates on 11Mbps

using 2.4 GHz frequency band. To improve the speed various versions of 802.11 were

introduced. 802.11a came with 54Mbps using 5GHz, 802.11g works on 2.4GHz frequency

providing 54 Mbps speed and then 802.11n operates on both 2.4 GHz and 5 GHz band proving

the speed of 300 Mbps [1].Wireless Networks are considered a better alternative to avoid wired

complexity of network. Some attractive characteristics of wireless network that prompt its usage

are as follows:

Mobility: Wireless networks provide flexibility of movement to the user. They can

access information anywhere along with their desk. They don’t require having a wired

connectivity.

Reachability: With the help of wireless networks, reachability among people is

increased. With wireless network communication becomes location independent and

availability of person becomes more.

Simplicity: Initial setup cost for wireless network is more, but the facilities provided by

the network overcome this cost. Utilization of networks gets increased. Moreover

wireless networks are easy to setup as compare to wired networks. Simplicity of wireless

networks also provides ease of use to its users.

Maintainability: Maintenance is one of the considerable factors to decide the cost. Being

a wireless system, the maintenance cost is not too much.

Roaming Services: Using a wireless network system you can provide service anywhere

any time including train, busses, aeroplanes etc.

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1.2 Classification of Wireless Network

Wireless standard 802.11 is categorized into two categories: Infrastructure based networks and

ad-hoc networks [24].

Figure 1: Classification of Wireless Network

1.3 Infrastructure Based Network

Infrastructure based networks consist of two levels: stationary and mobile level. The stationary

levels consist of fixed base stations. Mobile level consists of mobile nodes that communicate

through base stations. Master station is called access point. All the communication passes

through access points. Fixed base stations are also known as access points (AP). When any

mobile nodes have to communicate with others, it registers with the base stations. Generally base

station uses different radio frequencies to communicate with registered nodes [24].

Figure 2: Infrastructure Based Network

Wireless Network

Infrastructure Based Networks

Infrastructure-less Networks

Mobile Ad-hoc Networks

Vehicular Ad-hoc Network

Flying Ad-hoc Network

Wireless Sensors Networks

Wireless Mesh Networks

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1.4 Infrastructure less Network

Infrastructure based networks are very useful in day to day communications that involves

telephony services, internet access, online transactions, business deals etc. But there are

numerous applications for which infrastructure networks are not economical and feasible. Such

kind of applications requires rapid network setup and temporary networks. Infrastructure less

networks are collection of mobile nodes that communicate through common radio channel [24].

Figure 3: Infrastructure-Less Network

Infrastructure less networks differs from other networks due to the following characteristics.

Lack of fixed infrastructure

Dynamic topology

Multi-hop routing

Node heterogeneity

Link variability and Limited physical security

1.5 Wireless Sensor Networks

A wireless sensor network (WSN) is a collection of cooperative spatially distributed sensor

nodes that continuously monitor environmental conditions such as temperature, sound, pressure

etc. and transfer this collected information to the main location. In WSN, each sensor node is

equipped with a radio transceiver, microcontroller, electronic circuit and energy source. A

wireless sensor network consists of few to thousands of nodes that share information through

wireless channel. The application area of WSN ranges from smart home realization to large

rescue and battle operations. Once all the sensor nodes are deployed, they self-organize

themselves to form an appropriate network infrastructure [10]. Basic idea behind WSN is that

the capability of single sensor is not enough; combining multiple nodes will enhance the power

and complete the mission.

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1.6 Wireless Mesh Network

One of the emerged wireless technologies is wireless mesh networks. In these networks, nodes

are consists of mesh clients and mesh routers. Each node can act as router for forwarding packets

of other nodes. WMNs are considered to be self-organized and self-configured networks [5]. The

nodes automatically create connectivity among each other. So deployment is not very difficult.

The advantage of WMN over other networks is easy maintenance, tolerance, reliable behavior

and low up cost. WMN technology provides the always online anywhere and everywhere

provision. This technology has numerous advantages, e.g., broadband connection for home,

building automation, networking among enterprises, neighborhood network creation etc. These

features enable the integration of WMN with Wi-Fi, WiMAX and WiMedia.

1.7 Mobile Ad-hoc Network(MANET)

The concept of MANET came from the technology in 1970 “DARPA”. DARPA was a packet

radio network. Due to renewed interest and development the newer concept of MANET was

involved. A "mobile ad hoc network" (MANET) is a group of mobile nodes that are connected

through wireless communication channel. MANETs are the part of infrastructure less networks

which require no pre-configurations. Nodes are free to move in any direction due to which the

network topology changes frequently. Any node can join or leave the network as and when

required. Anytime and anywhere communication is offered by MANETs. These features

distinguish mobile ad-hoc networks from other networks. But for delay sensitive services, these

networks may not offer best services [4]. Challenging issues faced by MANETs are routing

along with improved quality of service parameters, security, power control and delay sensitivity.

Figure 4: Mobile Ad-hoc Network [3]

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Along with routing, following research issues are faced by mobile ad-hoc networks:

Topology Control: Due to high node mobility, the topology changes very frequently.

Control and management of topology is one of major concern in MANETs. A virtual

infrastructure is one possible alternative to physical infrastructure. This plays an

important role in routing, because responsible nodes for routing are reduced. Only the

nodes which are in virtual backbone are considered. Efficient and effective topology

control algorithms are required for MANETs.

Quality of Service: Routing in one of active area of research in MANET. This become

even more challenging when quality of service e.g. bandwidth, end to end delay, packet

loss ratio is concerned.

Mobile ad-hoc networks suffer from various attacks listed in Table 1. These attacks are

possibly occurring in FANETs as well.

Table 1: Common attacks on MANET [11]

MANET Layers Attacks

Multi-layer Attacks DoS, MIMA, Replay, Impersonation

Application layer Repudiation, data corruption

Transport layer Session hijacking, SYN Flooding

Network layer Link Spoofing, Black-hole, Worm-hole, Byzantine,

Route tracking, Message fabrication

Data link layer WEP weakness, disruption MAC(802.11), bandwidth

stealing, traffic monitoring

Physical layer Jamming, Intervention, Snooping

1.8 Vehicular Ad-hoc Network (VANET)

Now a day’s traffic management is one of the biggest problems faced by the world. Growing

volume of road traffic is affecting the safety and efficiency of the environment. To handle such

issues analysis of traffic is required. The entire vehicles on the roads are the mobile nodes; this

can be related to the mobile ad-hoc networks. Vehicular ad-hoc network (VANET) is a

subcategory of mobile ad-hoc networks (MANET) which was formed for traffic management by

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intelligent transportation system (ITS).VANET provides two ways of communication. First

method is purely wireless infrastructure less networks. Another method of communication is

through fixed infrastructure and vehicle. Fixed infrastructure is Road Side Units (RSUs) which

are stationary nodes that communicate mobile nodes i.e. vehicles. Vehicles are equipped with on

board units (OBU) and application units (AU) [14]. Road side units are connected to internet.

Figure 5: Vehicular Ad-hoc Network [14]

Vehicular ad-hoc network have various application as following:

Safety applications: VANETs are designed to provide security related applications.

Various applications in security domain are:

Collision avoidance

Traffic Management

Co-operative driving

User applications: VANETs can provide various other applications except security.

Electronic toll collection

Entertainment Applications

Internet Access

Locating fuel station

1.9 Flying Ad-hoc Network (FANET)

In case of calamitous event, when ordinary communication infrastructure is out of service or

simply not available, a group of small flying robots can provide a rapidly deployable and self-

managed ad-hoc Wi-Fi network to connect and co-ordinate rescue terms on ground [22]. The

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large degree of freedom and self-organising capabilities makes mobile ad-hoc networks totally

different from any other network solution. The communication standards proposed for ad-hoc

networks are not only liable to grounded networks, rather they also have wide application in

unmanned aerial vehicle networking (UAV). Further, UAV is an aircraft with no pilot on

board. UAVs can fly autonomously based on pre-programmed flight plans or can be operated

using complex dynamic automation systems and are versatile and flexible in implementation

[22]. Hence, UAV have wide application such as disaster management, location aware services,

rescue operations, security services etc. Single UAV based monitoring system already exists and

is particularly implemented. But, when a single UAV system is considered, it has always an issue

of network scalability and flexibility due to its limited surveillance capability and single UAV

[23]. Thus, in order to increase the capability of UAV controlled network, multi-UAV system is

required. In recent research work, UAV based ad-hoc networks are also termed as “Flying ad-

hoc network”. Flying ad-hoc networks are also sub category of mobile ad-hoc networks. These

networks are designed to overcome the issues faced by mobile ad-hoc networks. Setting up an

ad-hoc network in military area, battle fields, areas affected by natural disasters like earthquake,

flooding etc. is difficult. MANETs were not applicable for such situations. Flying ad-hoc

networks are infrastructure less networks with no central control. FANET uses micro air vehicles

(MAVs) for communication. Various MAVs form swarms and arrange themselves to

communicate in large area using wireless network. UAVs communicate with each other locally,

with base station and also interact with their environment to get information.It is capable to carry

on transmission without any centralized device [30].

Figure 6: Flying Ad-hoc Network

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Flying ad-hoc network have various application as following:

Calamity Administration: FANET is useful when the existing communication system is

damaged due to natural disaster like floods, earthquake, firing etc.

In Sensor Networks: Different sensor devices can be used to collect data to do daily

functions like weather forecasting, terrestrial movement tracking etc.

Location Aware Services: FANETs can be used in following services [22].

Forwarding calls to any location

Can act as travel guide for passengers

To identify information regarding specific location

Military Services: FANET are very useful in military services. Setting up proper

communication system is very difficult in military areas. So FANETs are used for

information exchange among soldiers, military headquarters.

Search and Rescue Operations: FANET can be used provide a better way to do search

and rescue operations such as rescue operation of hostages [22].

Security Purpose: FANET is capable of receiving information quickly. It can be used to

collect information for the security purpose of a delegate visiting to a place where no

network infrastructure exists.

1.10 Comparison among MANET, VANET and FANET

The comparison among MANETs, VANETs and FANETs is clearly stated in the survey which is

shown in Table 2.

Table 2: Comparison of different Ad-hoc Networks [30]

Parameter MANETs VANETs FANETs

Mobility Low High Very High

Nodal Density Low High Very Low

Mobility Model Random Regular Random

Topology Change Slow Fast Fast

Line of Sight Not Available In Some Cases Available

Localization GPS GPS, AGPS GPS, AGPS

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2. Literature Survey

2.1 Literature Review

MANET routing protocols were used by the researchers in the initial phase of FANET studies

and experiments. Literature survey of existing and new proposed secure routing techniques for

multi UAV ad-hoc networks by researchers.

In [6] M.T. Hyland et al. compared reactive, proactive and position based routing

techniques for FANET. They have taken AODV as reactive, OLSR as proactive and

GPSR as position based routing. It has been conclude the position based routing (GPSR)

out performed AODV and OLSR routing for swarm of UAV. Comparison is done on two

parameters, packet delivery ratio and end to end delay.

A unified framework is proposed by Otrok et al. in [7] for elongate the lifetime of a

cluster based IDS by balancing the resource consumption. The basic idea is to choose the

most efficient node for the detection process. The proposed framework was also able to

identify and punish misbehaving leader IDS that would deviate from intrusion detection.

A game theoretical model based on cooperative decision was proposed which can

effectively identify misbehaving leader-IDS with minimum false-positive rate. To

maximize the detection probability for leader-IDS, a zero-sum non-cooperative game was

also given. Leader-IDS play game with intruder without having the complete information

about the intruder. Results shows that proposed framework choose most efficient node

and maximize detection probability with less false-positive.

V. R. Khare et al. discussed the control model of unmanned air vehicle in [8]. A swarm

of UAVs is used to create FANET. To deal with dynamic and distributive nature of

problem, model has characteristics like self-organizing, distributive and decentralized.

Performance of routing improved because of physical propinquity of UAVs in the swarm

[8]. Khare also stated that dynamic source routing gives comparatively better

performance than proactive routing technique in highly dynamic node movement and

dynamic topology.

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J. T. Chang et al. Proposed a security suite for MANET routing named as VESS

(versatile extensible security suite) [12]. Security suite is proposed for AODV routing

protocol and mainly cover authentication and encryption aspects of security. In proposed

security suite digital cipher chaining is used for powerful authentication and different

ciphers DES, AES and RSA is used to provide user adjustable encryption. VESS have

four different encryption options: (Open, lightweight, strong and user). All the four

modes provide different level of security as {open- no encryption, lightweight- can be

cracked by brute force with high computation power, strong – highest security in VESS,

user- can be customize their own balance of security and performance. Network security

and performance is analyzed, only by adding 10-30% delay in network, VESS can

provide the strongest security to the network.

In [13] W.Lou et al. proposed a security scheme for dynamic MANETs named as Secure

Protocol for Reliable Data Delivery (SPREAD). The idea behind SPREAD is to transmit

message into small chunks through multipath routing. The message is divided into parts

and then transmits through multipath routing and if a small number of shares are

compromised then also it does not enable whole message to be compromised. A secret

sharing algorithm is used to divide a message into several parts so that adversary must

have to compromise at least T shares to compromise the whole message, where T is a

threshold value. Simulation Results depicts that if data is transmitting through insecure

network than SPREAD provides more secure data delivery. It is also shown that a

redundant SPREAD design can provide reliability without sacrificing the security.

In [15] S. Bhattacharya, and T. Basar Consider a differential game theoretic approach to

avoid jamming attack on the communication channel by computing an optimal strategies

with a team of UAVs. In their discussion they have consider two variation of the problem

as zero-sum pursuit evasion game and the other is used lsaacs. These two approaches are

used to derive the necessary condition to reach the saddle point strategies of the players.

Results are illustrated through simulation.

R. Ferdous et al. proposed a node based trust management technique for MANET in [16].

The proposed scheme uses a mobile agent system as a backbone for cluster-based

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wireless sensor network, which introduce trust between nodes locally. They have

assumed that trust is transitive and trust values are binary rather than continuous variable.

Trust value of node j can be calculated by node i in terms of two values. First trust value

of itself for node j by monitoring it and second is weighted sum of trust values calculated

by other nodes for node j in the network. Trust values calculated by other nodes consider

few parameters like (packets dropped by nj which is sent by nj, number of total packets

dropped by node nj, packets dropped by nj due to congestion, packets dropped by node nj

due to unidentified reasons, Priority given by node nj to its own packets vs other packets,

delay in packet forwarding by node nj due to {packets misrouted by nj and packets

falsely injected by nj}. NTM architecture consist three parts Trust Monitors (TMs), Node

Initiators (NIs) and Trust Evaluators (TEs). NTM node consist four components given as:

node id, wireless sensor, Trust Info-score and Context. Node Initiator generate a TM

agents with symmetric key (Sk) and a monotonically increase number which is

distributed to each node in the network through broadcasting. In case of old SK is stolen

or break, a new TM with new SK is launched by NI to avoid security breach. TM consist

three data structure trust evaluation table, message counter and history buffer. All TM

secure TE by using common SK and node cannot access it.

A. I. Alshbatat et al. proposed a new routing protocol for FANET called Directional

Optimized Link State Routing Protocol (DOLSR) [17] which uses directional antenna.

The proposed protocol is the extension of basic Optimized Link State Routing Protocol

(OLSR). The idea behind the DOLSR is to minimize the multi-point relays (MPR) with

the help of heuristic. Proposed routing scheme minimize the end-to-end delay and also

minimize the number of overhead packets. The results also show that DOLSR

outperformed OLSR, DSR and AODV in terms of overall throughput and as well as in

terms of end to end delay.

T. Eissa et al. proposed a model for identity based RSA scheme [19]. The scheme is

proposed for fast cryptographic operations for network performance. The basic idea is

that in RSA cryptographic scheme, all of the attacks are not possible if public key is not

available in the public domain or not known to the attacker. So, shorter RSA key can be

used safely for fast encryption and decryption. Proposed scheme works as: Initially all the

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nodes deployed with a identity which is known to the other nodes by using the friendship

concept for trusted nodes, then all nodes publish their public parameter in the network

and then node(A) encrypt its own public key by using given formula in [19] . After it A

sends its encrypted public key and RSA modulus. Receiver (B) decrypt public key of

node (A) by using given formula in [19]. Finally B can securely send a message to node

A by using its public key. They proved that proposed scheme is secure against IND-

CSPKA and RSA cryptanalysis attacks. The proposed scheme is compared with RSA-TC

and ECC-TC and shows better network performance.

In [20] S. Mutly, and G. Yilmaz proposed trust relationship based a cooperative intrusion

detection framework for MANETs. All the nodes observe their neighbor nodes for

suspicious activities. If a node detects unusual behavior of a neighbor node then it

broadcasts alert messages in the network. Trust management is depends upon

rebroadcasting of alert messages by the neighboring nodes. A reputation of alert

messages is used to calculate the trust level of a node. Framework is basically based on

direct neighbor observation, but indirect observations are also used. Framework also

provide robustness against false trust information transmit in the network by malicious

nodes. However, the performance of the trust management service is not analyzed, and

the framework does not present the classes of attacks that are possible to be detected.

In [21] a Hierarchical Identity-Based Encryption technique for mobile ad-hoc network is

proposed by H. Li which is based on Hierarchical Identity-Based Model. The proposed

Encryption technique is secure from different kind of security attacks. Proposed scheme

is based on lattice and reduced on learning with error (LWE) problem, which is a lattice-

hard problem defined by Regev. The LWE is resistant to quantum computing attacks, so

proposed encryption technique can be considered as secure against quantum computing

attacks. HIBEM is based on LWE and top-down approach. One level secret key discloser

does not enable attacker to get the other level key. Private Key transmission and

authentication is done locally in HIBEM to avoid bottleneck.

A spatial secure group communication (SSGC) problem is introduced and for deeply

investigates an analytical framework for multiple UAVs and SSGC is presented by S.W.

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Kim, and S.W. Seoin [25]. A distributed method is proposed to solve the problem, which

analyze spatial group size, upper bound of group member and stability. Especially

communication range and relative position also investigated to form closed group.

Feasibility of proposal is demonstrated with application scenario.

Different security threats for UAVs System are analyzed and a cyber-security threat

model has been proposed by A.Y. Javaid, et al. In [26]. A detailed security threat analysis

is done which provide an edge to the researcher, designer and users to identify

vulnerabilities in the UAVs system to find the counter-measures from them. Security is

very much important to UAVs system because the carry sensitive and confidential

information, threat to UAVs system can leads to national security issue. They have also

tried to evaluate risk generating by different vulnerabilities to the UAVs system.

In FANET, UAVs communication suffers data packets lost because of high movements

of nodes and very frequent changes in topology. So, there is a need of routing protocol

which can overcome from the packet loss. Lin et al. proposed Geographic Position

Mobility Oriented Routing (GPMOR) [27]. GPMOR uses Gauss-Markov mobility model

to predict the mobility pattern of UAVs to eliminate effect of high node movement. For

accurate decision in mobility pattern GPMOR uses Euclidean distance.

A distributed intrusion detection method with integration with an IDS is proposed by A.

Morais et al. In [28]. The proposed method relies on non-intrusive traffic monitoring at

each network node. An IDS is responsible for observing and monitoring the network

traffic at the node. An IDS is also responsible for exchanging routing events with

neighboring nodes to identify malicious activity. In the proposed mechanism a

modification is done in the popular BRO network IDS. Original BRO IDS have two

layers, Event engine and Policy script interpreter. Third layer Routing event analyzer is

added in proposed method. The nodes in neighborhoods participate in decision about a

node is malicious or not. A node is considered malicious if all participating nodes reach

at consensus. The proposed work is validating by implementing in virtualized network

environment.

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E. A. Panaousiset al. proposed a security model in [29] for MANETs for real-time

communication like emergency, rescue etc. proposed model consists intrusion detection

provision, secure routing protocol and security extension for communication with peer-

to-peer overlays. In model main emphasized on P2PSIP overlays. They have presented

and analyzed two extensions of the IETF drafts in terms of security. For real-time

emergency communications secure P2P overlays with IDS can provide a full and robust

solution. They have also discussed the use of IPSec in adaptive routing protocol and also

with its security extension. The results were compared with SAODV routing and been

measured more efficient in terms security and performance.

K. Hartmann, and C. Steup Carried out an assessment of security attacks consists of

vulnerability and threat analysis on the UAVs based communication systems and also

developed a risk assessment scheme for these UAVs based networks [31]. Various

parameters like communication system, exposure, sensors, storage media and fault

handling mechanism etc. The proposed approach is used to assessment of the currently

used UAVs such as: “MQ-9 Reaper” and “AR Drone”. Risk analysis of “RQ-170

Sentinel” is discussed.

In the paper [32] M.S. Faughnan, S. Michelle, et al. aim to achieve two objectives. First,

try to identify risk regarding cyber security attacks on a UAV and second, to develop a

scheme through which security breach is informed to the UAV operator. Established risk

assessment methods are used to achieve the first objective. To achieve second objective a

methodology is developed that measures velocity of UAV with the help of two on-board

systems and if any considerable variation occurs then it indicates a probable security

breach. To simulation of UAV flight is done through car movement to perform analysis

of experiment results.

K. Mansfield, et al. developed a threat model in [33] to observe and analyze cyber

security vulnerabilities in hardware, software, GCS networking hub, smart devices and

communication networks. It will help the users to secure communication. They have

focused physical connection, application software and operating system malware because

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these are the main target of attacker to get control over UAV or to steal the information

from the communication network.

M. Liu et al. developed an approach based on cognitive map building in which, cluster

heads are elected during routing phase that allows logical partitioning for better mobility

management of nodes [34].

S. Rosati et al. proposed an extension of basic Optimized Link-State Routing (OLSR)

protocol called Predictive-OLSR [36]. It is able to provide efficient routing in highly

dynamic environment. Predictive-OLSR uses GPS information and also calculates

expected transmission count (ETX) metric. ETX is the measurement of quality of links in

the ad-hoc network. The quality of link is calculated based upon the forward and

backward packet delivery ratio. Results of emulation at MAC layer shows that

Predictive-OLSR succeeds in providing an efficient and reliable routing in very highly

dynamic environment whereas BABEL and OLSR fails to do so.

In [37] T. V. P.Sundararajan et al. proposed a Behavioral based IDS for detecting

wormhole attack in MANETs. Proposed system uses hybrid negative selection detectors

to obtain information from the routing protocols. In BAIDS structure all the MANET

nodes are responsible and capable for detecting violating behavior but group of nodes

also can examine in its border range. BAIDS detectors detect good and bad behaving

nodes with good accuracy. Detectors observe deviation from expected or normal behavior

of nodes in the MANET. BAIDS performance for detecting wormhole attack is measured

under the three different MANET routing protocols given as AODV, DSR and DSDV.

Simulation experiments results have been shown.

Z. Birnbaum, et al. proposed a prototype system for UAV monitoring which provide

estimation of airframes and controller parameter and also capture flight data [38].

Captured data and estimated parameter compared with the already known standard

parameters. If there is any significant variation is observer between standard and capture

data, alert signal is send to ground control station and accordingly action taken. For

estimating the UAV parameters, Recursive Least Squares method is used. State space

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model and equation parameter are used in conjunction with proposed estimator. State of

the art flight simulator is used to test the system.

S. Amin et al. designed a secure framework for ADS-B surveillance system which is

dependent on digital communication between ground station and aircraft [39]. Three

different alternative techniques hashing, symmetric encryption and asymmetric

encryption are used to avoid spoofing attack on ADS-B surveillance system. Analysis of

all implications and collision risks is done by simulations which model the attack on

airspace.

In [40] A. Y. Javaid, et al. analyze the performance of simulation test-bed for security

aspect of wireless communication by performing DDoS and Jamming attacks on single

and multiple UAVs. Simulation is done on the UAVSim simulator proposed in [26].

S. Temel and I. Bekmezci present a MAC protocol named as LODMAC (Location

Oriented Directional MAC) in [41]. LODMAC uses neighbor nodes location estimation

and utilization of directional antennas within the MAC layer. LODMAC uses BTS (busy

to send) packet along with RTS (request to send) and CTS (clear to send) packets. Results

show that LODMAC outperforms directional MAC protocol.

In [42] V. Sharma and R. Kumar present an opportunistic network formation using cross

layer design for FANET. Service layer security of FANET is used in the presented

network model to provide parameterized input to neural setup. The proposed design

offers effective utilization of resource, high data delivery ratio and efficient service

coordination with lower delay to secure service.

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3. Research Gaps

3.1 Research Gaps

The basic idea behind FANET is same as MANET but there are certain differences like node

speed, topology change, mobility model etc. Hence, FANET faces some additional challenges al

than MANET. Based on the finding of literature review, following are the areas identified that

require significant research to be done:

i. Routing: Routing in FANET is different from other ad-hoc networks. Node movement is

relatively very high for flying ad-hoc networks. So the topology changes very frequently.

One of the biggest challenges for researchers is to suggest an efficient routing

algorithm that can work for high mobility nodes.

The routing algorithm should be quick to update its routing table frequently as the

topology changes [35].

ii. Security: To manage secure routing is another point of concern in FANET.

Ensuring Confidentiality, Integrity and Availability of valuable information in

FANET is another issue faced by these networks [9], [45].

Another issue faced by FANET is node compromise due to lack of physical security.

Risk to the network increases even more if the node is a centralized entity [2].

Trust Management among nodes is another challenge due to high topology changes.

Nodes join and leave the groups very frequently [44].

Existing routing algorithms for ad-hoc networks are impotent against frequent

network topology changes and malicious attacks in FANET.

iii. Quality of Service (QoS): Along with routing, the quality of service parameters should

also be improved. Data transition by FANETs includes images, videos, audios, text, GPS

locations etc. To transport such data performance should have a good quality with less

delays and error rates. [18].

iv. UAV Mobility and Placement: The placement of UAVs at appropriate location is one of

the major research concerns in FANETs. UAVs of different capacity and capability are

used for different purpose. Mini-UAVs are meant for carrying fewer payloads, like a

thermal camera, single radar, camera, image sensor, etc. So, this is an open challenge to

optimize the UAV placement to diminish energy feeding when the retrieved information

18

is taking more time.

v. Scalability: Single UAV system can perform limited tasks. To perform more number to

tasks, collection of UAVs is required. This motivated the concept of multi-UAV based

system. This improves performance, reduces delay and optimizes the task [43]. FANET

algorithms should be so designed that they can accommodate any number of UAVs.

vi. Reliable and secure data transfer: FANET applications transfer sensitive information.

So the reliability of the network should be very high. Reliability and security should be

defined with the criticality of data. So different level of security need to be defined.

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4. Problem Statement

4.1 Problem Statement

Existing routing protocols for ad-hoc networks experiences the serious issues in the area of

security. FANETs require routing algorithms that performs well with high mobility nodes and

rapid topology changes. Different research communities have highlighted security needs of

FANETs. This research aims to provide A Security Framework for FANETs that can calibrate

with rapid topology changing high mobility nodes for secure communication and trust

management. This framework will enhance the reliability on the critical applications area of

FANETs.

4.2 Objectives

On the basis of literature and research gap of work mention above, the following objectives have

been identified to be investigated under the research entitled on “A Security Framework for

Flying Ad-hoc Networks”.

1. To study and analyze the existing secure routing protocols/framework/schemes for

FANETs.

2. To design and develop a secure framework for FANETs.

3. To verify and validate the proposed secure framework.

4. To compare and evaluate it with other proposed secure protocols/framework/schemes.

4.3 Methodology

To achieve the objectives the research work will pass through the following phases:

1. A comprehensive investigation will be conducted to study various existing routing

protocols and their security in FANETs accomplished in depth learning of secure routing

techniques/framework in FANETs.

2. A secure framework will be proposed based upon the knowledge and information

acquired from the above phases. The proposed mechanism will address security issues

and will be evaluated on parameters like – delay, throughput, response time etc.

20

3. Proposed framework will be verified and validated based upon mathematical foundation

and simulation using synthetic data. Simulators like NS2, MATLAB, UAVSim etc.

4. The proposed framework will be compared with other proposed security frameworks

against parameters like efficiency, delay etc.

4.4 Work Plan

Activity 1

st Year 2

nd Year 3

rd Year

A

B

C

D

E

F

G

Activity

A. Study and review of existing security mechanism of various routing protocols for

FANETs.

B. Analyzing the proposed security framework against different security parameters such as

confidentiality, integrity, availability etc.

C. Design and development of a secure framework for FANETs.

D. Verification and Validation of the proposed security framework.

E. Compare the proposed framework few of the existing security mechanism.

F. Documentation and Thesis writing.

G. Publication of research work in conferences / journals.

21

References

[1] D. Bertsekas and R. Gallager, “Data Networks”, Prentice Hall, pp. 297-333, 1987.

[2] L. Zhou, andZ. J. Haas, “Securing ad hoc networks”, in: Network, IEEE,Vol.13, Issue 6,

24-30, 1999.

[3] D.Shukla, and Sridhar Iyer. "Mobility models in ad hoc networks."KReSIT, IIT

Bombay ,2001.

[4] J. Hoebeke, I. Moerman, B. Dhoedt and P. Demeester, “An Overview mobile ad-hoc

Network: Application and Challenges”, in 43rd

European Telecommunication Congress,

Ghent, Belgium, 2004.

[5] F. Akyildiz, X. Wang and W. Wang, “Wireless Mesh Network: A Survey” in Computer

Networks and ISDN Systems, Vol. 47, Issue 4, March 2005.

[6] M.T. Hyland, B.E. Mullins, R.O. Baldwin, M.A. Temple, “Simulation based performance

evaluation of mobile ad hoc routing protocols ina swarm of unmanned aerial vehicles”,

in: Proceedings of the 21stInternational Conference on Advanced Information

Networking and Applications Workshops , Vol. 02, AINAW ’07, IEEE Computer

Society, Washington, DC, USA, pp. 249–256,2007.

[7] Otrok, Hadi, N. Mohammed, L. Wang, M. Debbabi, and P. Bhattacharya. "A game-

theoretic intrusion detection model for mobile ad hoc networks."Computer

communications Vol. 31, Issue 4, 708-721,2008.

[8] V. R.Khare, F. Z. Wang, S. Wu, Y. Deng, and C. Thompson. "Ad-hoc network of

unmanned aerial vehicle swarms for search & destroy tasks." In Intelligent Systems,

2008.IS'08. 4th International IEEE Conference, Vol. 1, pp. 6-65, 2008.

[9] K. Sampigethaya, R. Poovendran, and L. Bushnell. "Security of future enabled aircraft

AD HOC networks." AIAA Aviation Technology, Integration and Operations (ATIO),

2008.

[10] J.Yick, B. Mukherjee, and D. Ghosal. "Wireless sensor network survey." Computer

networks , Vol. 52, Issue 12, pp. 2292-2330,2008.

[11] L. Abusalah, A. Khokhar, and M. Guizani."A survey of secure mobile ad hoc routing

protocols." Communications Surveys & Tutorials, IEEE, Vol. 10, Issue 4, pp. 78-93,

2008.

22

[12] J. T. Chang, S. Gundala, T.S. Moh, and M. Moh. "VESS: a Versatile Extensible Security

Suite for MANET Routing." InCommunications, Computers and Signal Processing,

2009.PacRim 2009.IEEE Pacific Rim Conference on, pp. 944-950, 2009.

[13] W.Lou, W. Liu, Y. Zhang, and Y. Fang. "SPREAD: Improving network security by

multipath routing in mobile ad hoc networks."Wireless Networks, Vol.15, Issue 3, pp.

279-294, 2009.

[14] H. Moustafa,and Yan Zhang. “Vehicular networks: techniques, standards, and

applications”. Auerbach publications, 2009.

[15] S. Bhattacharya, and T. Basar. "Game-theoretic analysis of an aerial jamming attack on a

UAV communication network."In American Control Conference (ACC), pp. 818-823,

2010.

[16] R. Ferdous, V. Muthukkumarasamy, and A. Sattar. "A node-based trust management

scheme for mobile ad-hoc networks." In Network and System Security (NSS), 2010 4th

International Conference on, pp. 275-280, 2010.

[17] A.I. Alshabtat, L. Dong, J. Li, and F. Yang."Low latency routing algorithm for unmanned

aerial vehicles ad-hoc networks." International Journal of Electrical and Computer

Engineering, Vol. 6, Issue 1, pp. 48-54,2010.

[18] E. Yanmaz, C. Costanzo, C. Bettstetter, and W. Elmenreich."A discrete stochastic

process for coverage analysis of autonomous UAV networks."In GLOBECOM

Workshops (GC Wkshps), 2010 IEEE, pp. 1777-1782, 2010.

[19] T. Eissa, S. A.Razak, and M. D. Ngadi."Towards providing a new lightweight

authentication and encryption scheme for MANET." Wireless Networks, Vol. 17, Issue 4,

pp. 833-842, 2011 .

[20] S. Mutly, and G. Yilmaz. "A distributed cooperative trust based intrusion detection

framework for MANETs." In ICNS 2011, The Seventh International Conference on

Networking and Services, pp. 292-298, 2011.

[21] H. Li. "A Hierarchical Identity-Based Encryption for MANETs." In Computational

Problem-Solving (ICCP), 2011 International Conference on, pp. 330-333, 2011.

[22] C. Zang, and S. Zang. "Mobility prediction clustering algorithm for UAV

networking."In GLOBECOM Workshops (GC Wkshps), 2011 IEEE, pp. 1158-1161,

2011.

[23] M. Müller. "Flying Ad-Hoc Networks." Institute of Media Informatics Ulm University,

Vol. 53, 2012.

23

[24] N. Saxena, and N. S. Chaudhari. "Message Security in Wireless Networks: Infrastructure

based vs. Infrastructure-less Networks." IEEE, New Jersey ,2012.

[25] S.W. Kim, and S.W. Seo."Cooperative unmanned autonomous vehicle control for

spatially secure group communications." Selected Areas in Communications, IEEE

Journal on 30, Vol. 5, pp. 870-882, 2012.

[26] A.Y. Javaid, W. Sun, V. K. Devabhaktuni, and M. Alam."Cyber security threat analysis

and modeling of an unmanned aerial vehicle system."In Homeland Security (HST), 2012

IEEE Conference on Technologies for, pp. 585-590.2012.

[27] L. Lin, Q. Sun, J. Li, and F. Yang. "A novel geographic position mobility oriented

routing strategy for UAVs." Journal of Computational Information Systems 8, Vol. 2, pp.

709-716, 2012.

[28] A. Morais, and A. Cavalli. "A distributed intrusion detection scheme for wireless ad hoc

networks."In Proceedings of the 27th Annual ACM Symposium on Applied Computing,

pp. 556-562, 2012.

[29] E. A. Panaousis, C. Politis, K. Birkos, C. Papageorgiou, and T. Dagiuklas."Security

model for emergency real-time communications in autonomous networks." Information

Systems Frontiers, Vol. 14, Issue 3, pp. 541-553, 2012.

[30] I. Bekmezci, O. K. Sahingoz, and Ş. Temel. "Flying ad-hoc networks (FANETs): a

survey." Ad Hoc Networks, Vol. 11, Issue 3, pp. 1254-1270, 2013.

[31] K. Hartmann, and C. Steup. "The vulnerability of UAVs to cyber attacks-An approach to

the risk assessment." In Cyber Conflict (CyCon), 2013 5th International Conference on,

pp. 1-23, 2013.

[32] M.S. Faughnan, B. J. Hourican, G. C. MacDonald, M. Srivastava, J. A. Wright, Y. Y.

Haimes, E. Andrijcic, Z. Guo, and J. C. White. "Risk analysis of Unmanned Aerial

Vehicle hijacking and methods of its detection." In Systems and Information Engineering

Design Symposium (SIEDS), 2013 IEEE, pp. 145-150, 2013.

[33] K. Mansfield, T. Eveleigh, T. H. Holzer, and S. Sarkani. "Unmanned aerial vehicle smart

device ground control station cyber security threat model." In Technologies for

Homeland Security (HST), 2013 IEEE International Conference on, pp. 722-728, 2013.

[34] M. Liu, J. Lin, and Y. Yuan."Research of UAV cooperative reconnaissance with self-

organization path planning."In International Conference on Computer, Networks and

Communication Engineering (ICCNCE 2013).Atlantis Press, 2013.

24

[35] O. K. Sahingoz. "Networking models in flying Ad-hoc networks (FANETs): Concepts

and challenges." Journal of Intelligent & Robotic Systems, Vol. 74, Issue 1-2, pp. 513-

527, 2014.

[36] S. Rosati, K. Kruzelecki, G. Heitz, D. Floreano, and B. Rimoldi. "Dynamic Routing for

Flying Ad Hoc Networks." arXiv preprint arXiv:1406.4399, 2014.

[37] T. V. P.Sundararajan, S. M. Ramesh, R. Maheswar, and K. R. Deepak."Biologically

inspired artificial intrusion detection system for detecting wormhole attack in

MANET." Wireless networks, Vol. 20, Issue 4, pp. 563-578, 2014.

[38] Z. Birnbaum, A. Dolgikh, V. Skormin, E. O'Brien, and D. Muller. "Unmanned Aerial

Vehicle security using Recursive parameter estimation." In Unmanned Aircraft Systems

(ICUAS), 2014 International Conference on, pp. 692-702, 2014.

[39] S. Amin, T. Clark, R. Offutt, and K. Serenko. "Design of a cyber-security framework for

ADS-B based surveillance systems." In Systems and Information Engineering Design

Symposium (SIEDS), 2014, pp. 304-309, 2014.

[40] A. Y. Javaid, W. Sun, and M.Alam. "EAI Endorsed Transaction.", 2015.

[41] S. Temel, and I. Bekmezci. "LODMAC: Location Oriented Directional MAC Protocol

for FANETs." Computer Networks, 2015.

[42] V. Sharma and R. Kumar. "Cross Layer Design For Secure Service Dissemination Over

Flying Ad Hoc Networks.", 2015.

[43] Y. Saleem, M. H. Rehmani, and S. Zeadally, Integration of Cognitive Radio Technology

with unmanned aerial vehicles: Issues, opportunities, and future research

challenges. Journal of Network and Computer Applications, Vol. 50, pp. 15-31, 2015.

[44] U. Khan, S. Agrawal, and S. Silakari. "A Detailed Survey on Misbehavior Node

Detection Techniques in Vehicular Ad Hoc Networks." In Information Systems Design

and Intelligent Applications, Springer India, pp. 11-19. 2015.

[45] W. S. Yap, J. K. Liu, S. Y. Tan, and B.M. Goi."On the security of a lightweight

authentication and encryption scheme for mobile ad hoc network."Security and

Communication Networks, 2015.