A Novel Framework for LBS Privacy Preservation in Dynamic Context Environment

ACOMP 2011A Novel Frameworkfor LBS Privacy Preservationin Dynamic Context EnvironmentOulinePrivacy Concern Location-based Services in environment of dynamic contextA system of Privacy Preserving and EvaluatingThe proposed FrameworkModule evaluation and suggestionsConclusion2Mu l phn t ko hiu hoc ko r .2Location-based service: Definition3In an abstract wayA certain service that is offered to the users based on their locationsMu xu qu3Location-based service: Everywhere4Location-based traffic reports:What is the estimated time travel to reach my destination?Location-based store finder:Where is my nearest fast food restaurant?What are the restaurants within two miles of my location?Location-based advertisement:Send E-coupons to all customers within five miles of my store.

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4Location-based service: EverybodyPeople need GPS-equipped device to entertain LBS5

Draw more and more people, business attentionFast growing with variety of servicesContext involve flourish the value added servicesLocation based service: Now6

Cu ny cha hiu r6Location-based service becoming context-aware service 7

Privacy concerns in LBS8Some risk types ...New technology promise convenience but threaten privacy and securityEnabling context in LBS make evaluating privacy techniques more complicatedDifferent services require different techniquesChoice of algorithms varies according to current contextS nhiu hay t? Chia ng t lun.8Privacy concenrns in LBS (cont.)9

New technologies can pinpoint your location at any time and place. They promise safety and convenience but threaten privacy and security Cover story, IEEE Spectrum, July 2003 YOU ARE TRACKED!!!!

Key Problem10Users want to entertain LBS without revealing their sensitive informationService providers mission:provide suitable privacy techniques concerning user current context provide good output privacy levelrobust enough to protect users informationensure service qualityApproach Service Provider problem11Motivation: offer the ability of privacy preserving and evaluating to service providerApproach: employ existing privacy preserving algorithmevaluate privacy result of their outputsmodify the outputs (if necessary)Privacy algorithmEvaluatingRefiningLocation privacy algorithms 12Location obfuscationie. Location pertubation

Location privacy algorithms13Location k-anonymity

10-anonymity

Model for LBS algorithm evaluating14Attack models categorized on adversary background knowledgeAttack exploting Quasi-IndentifiersSnapshot or Historical attackSingle or Multiple-Issuer AttackAttack exploiting Knowledge of the DefenseValue the defense by metric:Snapshot, single-issuer, def-aware attack: reciprocityHistorical, single-issuer attack:memorization (i.e. historical k-anonymity)Mutiple issuers attack: m-invariance

Related works15An index-based privacy preserving service trigger by Y. Lee, O.Kwon

Related works16An index-based privacy preserving service trigger by Y. Lee, O. Kwon []AdvantageEasy implementation & good performanceDisadvantagesData mostly based on user feelingStatic context, lack of context managent methodRelated works17CARE Middleware

Related works18CARE MiddlewareAdvantagesManage context effeciently and dynamicallyResults can be used directly for privacy algorithmScalabilityDisadvantage: y ch l cung cp c ch qun l thng tin ng cnh. Cn b phn cung cp privacy v nh gi th cha c.18Middleware as base architecture19Location-based Database Server

LBS Middleware

Privacy-aware Query ProcessorThird trusted party that is responsible on blurring the exact location information. High computation capability collect context Locationet, scalability19Middleware as base architecture20

The proposed framework21

Context Aggregation22Context data collected from Profile Managers automatically and up to date.Capacle of solving conflict between policies of user, service provider and others.Context Aggregation23

Case based calculation24Checking reciprocity property

Case based calculation25

Ontology Reasoner26Checking memorization and m-inVariance propertiesConnect to Profile Managers & retrieve in-the-need dataOntology Reasoner27

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