The goal of this thesis is to study threats represented by multiplication and leaks of personal geolocated data. A first problem is conception of privacy-preserving geolocated systems. Actual technologies (e.g. bluetooth, WiFi) rely on protocols leaking sensitive pieces of information about their users. This can lead to identification of important places for people (home, work, etc.), prediction of future movements, learning of journeys’ semantic or inference of social relationships.
A second problem is conception of privacy-preserving data dissemination system in a
mobility context. The architecture set up by the trace collecting system deployed by the
Priva’Mov project, to which this thesis is attached, will allow to test efficiency of proposed solutions in a real environment.
A third problem is investigation of privacy-preserving access mechanisms to mobility traces. We want to propose efficient techniques to anonymize and access sequential data while offering strong anonymity guarantees. This requires to find a trade-off between data utility for data analysts and privacy protection for people appearing in traces.