A location privacy preserving algorithm for mobile LBS

Location-Based Service (LBS) combined with mobile devices and Internet become more and more popular, and are widely used in traffic navigation, intelligent logistics and the point of interest query. However, most users worry about their privacy when using the LBS because they should provide their accurate location and query content to the untrustworthy server. Therefore, how to protect users´ privacy is very important to the mobile LBS application. Continuous queries tracking attack is one of the typical attack models in mobile LBS. This paper analyzes the query association attack model for the continuous query in mobile LBS, formalizes the background knowledge of attackers considering the spatiotemporal dimension. In order to resist the query association attack for continuous query in mobile LBS, this paper improves the k-sharing model and proposes the location distribution aware cloaking algorithm which is distribution-aware when generating cloak regions, it satisfies the m-invariant and l-diversity. Finally, a set of experiments show the effectiveness of the approach.