A context-aware scheme for privacy-preserving location-based services

  • Authors:

  • Aniket Pingley;Wei Yu;Nan Zhang;Xinwen Fu;Wei Zhao

  • Affiliations:

  • Department of Computer Science, The George Washington University, Washington, DC 20052, USA;Department of Computer and Information Sciences, Towson University, Towson, MD 21252, USA;Department of Computer Science, The George Washington University, Washington, DC 20052, USA;Department of Computer Science, University of Massachusetts Lowell, Lowell, MA 01854, USA;Department of Computer and Information Science, University of Macau, Macau, China

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2012

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Abstract

We address issues related to privacy protection in location-based services (LBSs). Most existing privacy-preserving LBS techniques either require a trusted third-party (anonymizer) or use cryptographic protocols that are computationally and communicationally expensive. Our design of privacy-preserving techniques is principled on not requiring a trusted third-party while being highly efficient in terms of time and space complexities. The problem has two interesting and challenging characteristics: First, the degree of privacy protection and LBS accuracy depends on the context, such as population and road density, around a user's location. Second, an adversary may violate a user's location privacy in two ways: (i) based on the user's location information contained in the LBS query payload and (ii) by inferring a user's geographical location based on the device's IP address. To address these challenges, we introduce CAP, a context-aware privacy-preserving LBS system with integrated protection for both data privacy and communication anonymity. We have implemented CAP and integrated it with Google Maps, a popular LBS system. Theoretical analysis and experimental results validate CAP's effectiveness on privacy protection, LBS accuracy, and communication QoS (Quality-of-Service).