Location Privacy Protection for Smartphone Users Using Quadtree Entropy Maps

The ever-increasing popularity of location-based services (LBSs) poses a serious threat to users’ location privacy. Numerous efforts have been made to protect users’ location privacy and also to limit the degradation of service quality resulting from the additional protection layer. Most existing work, however, relies on a trusted anonymization server, which can itself become one source of untrustworthiness. In this paper, we present EMP—a new location privacy protection scheme based on a quadtree entropy map that enables users to protect their location privacy relying only on their smartphones. EMP reduces the trusted computing base (TCB) and is cost-effective, because it eliminates the requirement of a trusted server from the protection system. In addition, EMP accurately estimates the uncertainty of users’ intended destinations from an adversary’s perspective, and can properly adjust the protection level to defend against sophisticated inference attacks based on the correlation of user queries. Our evaluation of a prototype implementation demonstrates that EMP can effectively protect users’ location privacy with reasonable computation time and resource consumption. EMP complements the common trusted-server-based protection mechanisms and provides smartphone users a secure environment for their use of LBSs.