Privacy-Preserving Sharing of Sensitive Semantic Locations under Road-Network Constraints

This paper presents a privacy-preserving framework for the protection of sensitive positions in real time trajectories. We assume a scenario in which the sensitivity of user´s positions is space-varying, and so depends on the spatial context, while the user´s movement is confined to road networks and places. Typical users are the non-anonymous members of a geo-social network who agree to share their exact position whenever such position does not fall within a sensitive place, e.g. a hospital. Suspending location sharing while the user is inside a sensitive place is not an appropriate solution because the user´s stopovers can be easily inferred from the user´s trace. In this paper we present an extension of the semantic location cloaking model [1] originally developed for the cloaking of non-correlated positions in an unconstrained space. We investigate different algorithms for the generation of cloaked regions over the graph representing the urban setting. We also integrate methods to prevent velocity-based linkage attacks. Finally we evaluate experimentally the algorithms using a real data set.