Nearest Neighbor Queries with Location Privacy

Abstract

AbstractIn 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.KeywordsLocal PrivateCloaking RegionPoints Of Interest (POIs)Mobile UsersTotal Computation ComplexityThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.