A distortion-based metric for location privacy

Abstract

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. By using the proposed model, we provide formal representations of four metrics among the most relevant categories of location privacy metrics. 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 the 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 estimates location privacy as the expected distortion in the reconstructed users' trajectories by an adversary.