P2-CTM: privacy preserving collaborative traffic monitoring

Amro, Belal Mohammed and Saygın, Yücel and Levi, Albert (2010) P2-CTM: privacy preserving collaborative traffic monitoring. In: 3rd ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS (SPRINGL '10), San Jose, CA, USA

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Official URL: http://dx.doi.org/10.1145/1868470.1868483


Collaborative Traffic Monitoring (CTM) systems exploit the location information continuously collected from cars. Users collaborate by providing their location information to have a global picture of the current traffic in real-time. However, location is very sensitive information. Therefore, privacy is a major obstacle for the widespread usage of CTM systems. In this paper, we present our position for a novel system addressing the security and especially privacy problems of CTM systems. Existing CTM solutions generally use two different methodologies. The first one is the dedicated infrastructure approach, also called VANETs (Vehicular Ad Hoc Networks), where a dedicated infrastructure for communication is deployed. The second methodology utilizes existing wireless networks, such as GSM, GPRS, EDGE, UMTS and Wi-Fi. Our P2-CTM (Privacy Preserving CTM) approach combines the best parts of these two existing approaches. In order to address the privacy challenge in CTM systems, we propose a privacy preserving location update mechanism that meets the requirements of both traffic monitoring and map generation. A privacy metric is adopted to evaluate the location update mechanism. We also discuss the performance issues regarding the location update mechanism. We aim to have a sound indication for our system from the points of view of privacy, security and performance.

Item Type:Papers in Conference Proceedings
Uncontrolled Keywords:Collaborative Traffic Monitoring Systems, Location based Services, Privacy, Security, Public Key Cryptography, Networks, Traffic Monitoring
ID Code:15799
Deposited By:Albert Levi
Deposited On:10 Dec 2010 11:29
Last Modified:29 Jul 2019 11:33

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