A Distortion-based Metric for Location Privacy

We propose a novel framework for measuring and evaluating location privacy preserving mechanisms in mobile wireless networks. Within this framework, we first present a formal model of the system, which provides an efficient representation of the network users, the adversaries, the location privacy preserving mechanisms and the resulting location privacy of the users. This model is general enough to accurately express and analyze a variety of location privacy metrics that were proposed earlier. We provide formal representations of four among the most relevant categories of location privacy metrics, by using the proposed model. We also present a detailed comparative analysis of these metrics based on a set of criteria for location privacy measurement. Finally, we propose a novel and effective metric for measuring location privacy, called distortion-based metric, which satisfies these criteria for privacy measurement and is capable of capturing the mobile users' location privacy more precisely than the existing metrics. Our metric measures location privacy as the expected level of distortion of the adversary's hypothesized trajectories of the users, considering the adversary's knowledge and also the observed parts of the users' trajectories.