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    Zhou Changli, Ma Chunguang, Yang Songtao. Location Privacy-Preserving Method for LBS Continuous KNN Query in Road Networks[J]. Journal of Computer Research and Development, 2015, 52(11): 2628-2644. DOI: 10.7544/issn1000-1239.2015.20140532
    Citation: Zhou Changli, Ma Chunguang, Yang Songtao. Location Privacy-Preserving Method for LBS Continuous KNN Query in Road Networks[J]. Journal of Computer Research and Development, 2015, 52(11): 2628-2644. DOI: 10.7544/issn1000-1239.2015.20140532

    Location Privacy-Preserving Method for LBS Continuous KNN Query in Road Networks

    • Location privacy preservation and query service quality are a pair of contradiction in location based service (LBS). In the road network, there are a lot of limiting factors to be considered for continuous query. How to protect location privacy efficiently and acquire accurate continuous query results of places of interest (POIs) are great challenges in the road network. In this paper, based on the idea of using fake location, a query algorithm is proposed firstly, which picks the intersections of the road network gradually to form an anchor sequence to query POIs, and the query algorithm can not only achieve location privacy preservation but also deduce accurate K nearest neighbor (KNN) query results. And then, based on the idea of sending fake queries and constructing query anonymity group, a trajectory privacy preservation algorithm is proposed, which is used to resist continuous query correlation attack and movement model inference attack. At last, a discussion about the trade-off between privacy preservation and query service quality is given in the road networking LBS. The performance analysis and experiments show that our methods provide strong location privacy preservation and get accurate query results in the road network, and our algorithms have favorable timeliness and well-balanced data communication overhead.
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