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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...
Location based queries are increasingly common in mobile applications, and the associated privacy issues have become a hot research topic in the last years. Most of the current approaches, however, do not account for the location of potentially sensitive places and for constraints on the movement of users, such as speed limits or network contraints. In this demo we present different deployment scenarios...
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