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A Location Privacy Preserving Method Based on Sensitive Diversity for LBS

Abstract : A user’s staying points in her trajectory have semantic association with privacy, such as she stays at a hospital. Staying at a sensitive place, a user may have privacy exposure risks when she gets location based service (LBS). Constructing cloaking regions and using fake locations are common methods. But if regions and fake positions are still in the sensitive area, it is vulnerable to lead location privacy exposure. We propose an anchor generating method based on sensitive places diversity. According to the visiting number and peak time of users, sensitive places are chosen to form a diversity zone, its centroid is taken as the anchor location which increases a user’s location diversity. Based on the anchor, a query algorithm for places of interest (POIs) is proposed, and precise results can be deduced with the anchor instead of sending users’ actual location to LBS server. The experiments show that our method achieves a tradeoff between QoS and privacy preserving, and it has a good working performance.
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Changli Zhou, Chunguang Ma, Songtao Yang, Peng Wu, Linlin Liu. A Location Privacy Preserving Method Based on Sensitive Diversity for LBS. 11th IFIP International Conference on Network and Parallel Computing (NPC), Sep 2014, Ilan, Taiwan. pp.409-422, ⟨10.1007/978-3-662-44917-2_34⟩. ⟨hal-01403110⟩

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