An anonymous entropy-based location privacy protection scheme in mobile social networks

The popularization of mobile communication devices and location technology has spurred the increasing demand for location-based services (LBSs). While enjoying the convenience provided by LBS, users may be confronted with the risk of privacy leakage. It is very crucial to devise a secure scheme to protect the location privacy of users. In this paper, we propose an anonymous entropy-based location privacy protection scheme in mobile social networks (MSN), which includes two algorithms K-DDCA in a densely populated region and K-SDCA in a sparsely populated region to tackle the problem of location privacy leakage. The K-DDCA algorithm employs anonymous entropy method to select user groups and construct anonymous regions which can guarantee the area of the anonymous region formed be moderate and the diversity of the request content. The K-SDCA algorithm generates a set of similar dummy locations which can resist the attack of adversaries with background information. Particularly, we present the anonymous entropy method based on the location distance and request contents. The effectiveness of our scheme is validated through extensive simulations, which show that our scheme can achieve enhanced privacy preservation and better efficiency.