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Nearest Neighbor Queries with Location Privacy

  • Xun Yi
  • Russell Paulet
  • Elisa Bertino
Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

In mobile communication, spatial queries pose a serious threat to user location privacy because the location of a query may reveal sensitive information about the mobile user. In this chapter, we consider k nearest neighbor (kNN) queries where the mobile user queries the location-based service (LBS) provider about k nearest points of interest (POIs) on the basis of his or her current location. We described a solution given by Yi et al. [22] for the mobile user to preserve his or her location privacy in kNN queries. The solution is built on the Paillier public-key cryptosystem 11] and can provide both location privacy and data privacy. In particular, the solution allows the mobile user to retrieve one type of POIs, for example, k nearest car parks, without revealing to the LBS provider what type of points is retrieved. For a cloaking region with n × n cells and m types of points, the total communication complexity for the mobile user to retrieve a type of k nearest POIs is O(n + m) while the computation complexities of the mobile user and the LBS provider are O(n + m) and O(n 2 m), respectively. Compared with existing solutions for kNN queries with location privacy, these solutions are more efficient.

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Copyright information

© Xun Yi, Russell Paulet, Elisa Bertino 2014

Authors and Affiliations

  • Xun Yi
    • 1
  • Russell Paulet
    • 2
  • Elisa Bertino
    • 3
  1. 1.RMIT University Computer Science & Info TechMelbourneAustralia
  2. 2.Victoria UniversityMelbourneAustralia
  3. 3.Computer SciencePurdue UniversityWest LafayetteUSA

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