Location anonymization using real car trace data for location based services

Due to the popularization of location based services (LBSs), preserving user's location privacy has become a significant issue. In this paper, we assume that users are traveling by car and propose a location anonymization method which mainly aims at reducing traceability of user's movement trajectory. Since the movement patterns of car-driving users have some special characteristics due to various factors such as traffic rules, generating dummies in an artificially-synthesized manner is not practical. Therefore, in our method, we use real car trace data which were obtained from probe cars to generate dummies so that the generated dummies look like real users. In doing so, our method tries to find real traces which can cross with the user or another dummy at an intersection in order to reduce the user's traceability. Through simulations, we confirm that our method can reduce the traceability of the user's trajectory compared with some naive approaches.