Measuring long-term location privacy in vehicular communication systems

  • Authors:

  • Zhendong Ma;Frank Kargl;Michael Weber

  • Affiliations:

  • Institute of Media Informatics, Ulm University, Albert-Einstein-Allee 11, 89081 Ulm, Germany;Distributed and Embedded Security, University of Twente, P.O.-Box 217, 7500 AE Enschede, The Netherlands;Institute of Media Informatics, Ulm University, Albert-Einstein-Allee 11, 89081 Ulm, Germany

  • Venue:
  • Computer Communications
  • Year:
  • 2010

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Abstract

Vehicular communication systems are an emerging form of communication that enables new ways of cooperation among vehicles, traffic operators, and service providers. However, many vehicular applications rely on continuous and detailed location information of the vehicles, which has the potential to infringe the users' location privacy. A multitude of privacy-protection mechanisms have been proposed in recent years. However, few efforts have been made to develop privacy metrics that can provide a quantitative way to assess the privacy risk, evaluate the effectiveness of a given privacy-enhanced design, and explore the full possibilities of protection methods. In this paper, we present a location privacy metric for measuring location privacy in vehicular communication systems. As computers do not forget and most drivers of motor vehicles follow certain daily driving patterns, if a user's location information is gathered and stored over a period of time, e.g., weeks or months, such cumulative information might be exploited by an adversary performing a location privacy attack to gain useful information on the user's whereabouts. Thus to precisely reflect the underlying privacy values, in our approach we take into account the accumulated information. Specifically, we develop methods and algorithms to process, propagate, and reflect the accumulated information in the privacy measurements. The feasibility and correctness of our approaches are evaluated by various case studies and extensive simulations. Our results show that accumulated information, if available to an adversary, can have a significant impact on location privacy of the users of vehicular communication systems. The methods and algorithms developed in this paper provide detailed insights into location privacy and thus contribute to the development of future-proof, privacy-preserving vehicular communication systems.