PRIVACY AWARE COLLABORATIVE TRAFFIC MONITORING VIA ANONYMOUS ACCESS AND AUTONOMOUS LOCATION UPDATE MECHANISM
Computer Science and Engineering, PhD. Thesis, 2012
Assoc. Prof. Dr. Yücel Saygın (Thesis Supervisor), Assoc. Prof. Dr. Albert Levi (Thesis co-supervisor), Assist. Prof. Dr. Ali İnan, Assist. Prof. Dr. Ercan Nergiz, Assoc. Prof. Dr. Özgür Gürbüz
Date &Time: August 2nd , 2012 - 15:00
Place: FENS G032
Keywords: Collaborative Traffic Monitoring, Anonymous Access, Privacy, Anonymity , Location Based Services.
Collaborative Traffic Monitoring, CTM, systems collect information from users in the aim of generating a global picture of traffic status. Users send their location information including speed and directions, and in return they get reports about traffic in certain regions. There are two major approaches for the deployment of CTM systems. The first approach relies on dedicated communication infrastructure (DI). This approach is still being investigated by researchers and there is no important deployments done yet. The other approach utilizes existing communication infrastructures (EI) such as Wi-Fi, GSM, and GPRS for communication between users and traffic server.
Due to the sensitivity of location information, privacy preserving mechanisms should be considered during the design of CTM systems. In this thesis, we propose a Privacy Aware Collaborative Traffic Monitoring System (PA-CTM) that considers the privacy and security properties of VANETs and existing infrastructures. PA-CTM provides a client server architecture that relies on existing infrastructures and enhances privacy by (1) Using a robust Collusion Resistant Pseudonym Providing System, CoRPPS, for anonymous access. Users are able to change their pseudonyms and hence hide their complete trajectory information form traffic server; (2) Utilizing a novel Autonomous Location Update Mechanism, ALUM, that does not rely on a Trusted Third Party and uses only local parameters (speed and direction) for triggering a location update or pseudonym change. Our performance results showed that CoRPPS provides a high level of anonymity with strong resistant against collusion attacks. Performance results also showed that ALUM is effective for traffic monitoring in terms of both privacy and utility.