Abstract
Applying the proliferated location-based services (LBSs) to social networks has spawned mobile social network (MSN) services that allow users to discover potential friends around them. While enjoying the convenience of MSN services, the mobile users also are confronted with the risk of location disclosure, which is a severe privacy preserving concern. In this paper, we focus on the problem of location privacy preserving in MSN. Particularly, we propose a repartitioning anonymous region for location privacy preserving (RPAR) scheme based on the central anonymous location which minimizes the traffic between the anonymous server and the LBS server while protecting the privacy of the user location. Furthermore, our scheme enables the users to get more accurate query results, thus improving the quality of the location service. Simulation results show that our proposed scheme can effectively reduce the area of anonymous regions and minimize the traffic.
Highlights
Internet of Things (IoT), a trend of future networks, is immersed into many aspects of our personal and working lives and provides more comprehensive intelligent service
Social networks widely used in mobile Internet catalyze mobile social networks (MSNs), and users in MSN can acquire their own location information and sign in a location and find nearby friends and access to location-based services (LBSs) such as finding the nearest hotel, finding directions, sharing action tracks, obtaining information of body area networks, and so on [1,2,3,4,5,6,7]
When we enjoy the convenience of LBS and MSN services, the mobile users are confronted with the risk of location disclosure, which is a severe privacy preserving concern [8,9,10,11,12]
Summary
Internet of Things (IoT), a trend of future networks, is immersed into many aspects of our personal and working lives and provides more comprehensive intelligent service. When we enjoy the convenience of LBS and MSN services, the mobile users are confronted with the risk of location disclosure, which is a severe privacy preserving concern [8,9,10,11,12]. Analyzing the users’ locations and trajectories can better support MSNS and recommended services, it is easier for attackers to attack the user’s location information so as to expose user’s privacy. We focus on the location privacy preserving in MSN aiming at larger communication overhead, larger range, and inaccuracy of query results for traditional anonymous schemes. (1) We propose a repartitioning anonymous region for location privacy preserving (RPAR) scheme based on the central anonymous location. RPAR minimizes the communication traffic between the anonymous server and the LBS server while protecting the privacy of the user location.
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