Towards a scalable model for location privacy

  • Authors:
  • Nayot Poolsappasit;Indrakshi Ray

  • Affiliations:
  • Colorado State University, Fort Collins, CO;Colorado State University, Fort Collins, CO

  • Venue:
  • SPRINGL '08 Proceedings of the SIGSPATIAL ACM GIS 2008 International Workshop on Security and Privacy in GIS and LBS
  • Year:
  • 2008

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Abstract

With the growth of wireless and mobile technologies, we are witnessing an increase in location-based services (LBS). Although LBS provide enhanced functionalities, they open up new vulnerabilities that can be exploited to cause security and privacy breaches. Specifically, location data of individuals that are used by such services must be protected from security and privacy breaches. Such services will require new models for expressing privacy preferences for location data and mechanisms for enforcing them. We identify the factors on which location privacy depends and propose a scalable model for expressing privacy that can be used for LBS and other applications where the privacy of location information must be protected.