Privacy-Preserving Trajectory Collection

In order to provide context--aware Location--Based Services, real location data of mobile users must be collected and analyzed by spatio--temporal data mining methods. However, the data mining methods need precise location data, while the mobile users want to protect their location privacy. To remedy this situation, this paper first formally defines novel location privacy requirements. Then, it briefly presents a system for privacy--preserving trajectory collection that meets these requirements. The system is composed of an untrusted server and clients communicating in a P2P network. Location data is anonymized in the system using data cloaking and data swapping techniques. Finally, the paper empirically demonstrates that the proposed system is effective and feasible