Geo-indistinguishability: Differential privacy for location-based systems

The growing popularity of location-based systems, allowing un-known/untrusted servers to easily collect huge amounts of informa-tion regarding users ’ location, has recently started raising serious privacy concerns. In this paper we introduce geo-indistinguisha-bility, a formal notion of privacy for location-based systems that protects the user’s exact location, while allowing approximate in-formation – typically needed to obtain a certain desired service – to be released. This privacy definition formalizes the intuitive notion of protect-ing the user’s location within a radius r with a level of privacy that depends on r, and corresponds to a generalized version of the well-known concept of differential privacy. Furthermore, we present a mechanism for achieving geo-indistinguishability by adding con-trolled random noise to the user’s location. We describe how to use our mechanism to enhance LBS appli-cations with geo-indistinguishability guarantees without compro-mising the quality of the application results. Finally, we compare state-of-the-art mechanisms from the literature with ours. It turns out that, among all mechanisms independent of the prior, our mech-anism offers the best privacy guarantees