A Novel Time-Obfuscated Algorithm for Trajectory Privacy

Abstract

Location-based services (LBS) which bring so much convenience to our daily life have been intensively studied over the years. Generally, an LBS query processing can be categorized into snapshot and continuous queries which search on user location information and reply search results to the users. An LBS has full control to the location information, causing a user privacy concern. If an LBS has a malicious intention to infer the user privacy by tracking the user's routes to their destinations, it incurs a serious problem. In this paper, we propose a comprehensive trajectory privacy technique and combined ambient conditions to cloak location information based on the user privacy profile. We first propose a r-anonymity concept which preprocesses a set of similar trajectories R to blur the actual trajectory of a user. We then combine k-anonymity with s road segments to protect the user privacy. We introduce a novel time-obfuscated technique which breaks the sequence of the query issuing time for a user to confuse the LBS from knowing the user trajectory by sending a query randomly from a set of locations residing at the trajectories R. Despite the randomness incurring from the obfuscation process for providing a strong trajectory privacy protection, the experimental results showed that our trajectory privacy technique maintained the correctness of the query results at a competitive computational cost.