Differentially location privacy

Abstract

The Global Positioning System (GPS) module has become a de-facto standard in cell phones and many mobile devices in recent years, hence the booming of location-based services (LBSs) which provide a variety of information services based on location data. As all the LBS providers require the collection and access permission to users’ personal location data, severe privacy concerns are raised at the same time. Therefore, effective privacy preservation is foremost for LBS applications. This chapter presents three methods that apply differential privacy to achieve location privacy for LBSs: the geo-indistinguishability method, the synthetic differentially private trajectory publishing method, and the hierarchical location data publishing method, with an emphasis on the last one. The core of the hierarchical location data publishing method is a private location release algorithm called PriLocation for privacy preserving in location data release. Three private operations, private location clustering, cluster weight perturbation and private location selection, are used by the algorithm to ensure that each individual in the releasing dataset cannot be re-identified by an adversary.