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Time-Aware Dummy-Based Privacy Protection for Continuous LBSs

The flourishing of intelligent mobile devices, significantly prompts various location-Based Services (LBSs), especially continuous LBSs. However, continuous LBSs can suffer from location association attacks and trajectory attacks. The existing dummy-based schemes aren't protect users' privacy effectively since ignoring the reasonability of dummies. Therefore, in this paper we consider the Time-Sensitive Side Information(TSSI), spatiotemporal correlations and movement patterns of previous locations simultaneously to present a Dummy Filtering Algorithm(DFA). First we consider the TSSI to generate dummies. Then we propose two constraints time reachability and out-degree/indegree to cut off spatiotemporal correlations. Next, we utilize area overlapping and trend similarity to protect users' trajectory privacy. Security analysis indicates that our scheme can assure dummies' rationality and availability. Furthermore, experiments show that our scheme not only defends location association attacks and trajectory attacks effectively, but increases the ratio of available dummies from 42% up to 66.7%.