Trajectory-Differential Privacy-Protection Method with Interest Region

Trajectory data privacy protection method is a hot topic in data privacy protection research field. Most of existing trajectory data privacy protection methods adopt the strategy of adding noise to all locations, which reduces the availability of data after protection while protecting trajectory data. Aiming to solve this problem, this paper proposes a trajectory-differential privacy-protection method with interest region. In this method, an area where a user stays long enough within a certain distance range is defined as interest region. And the corresponding central point of the interest region is defined as stay point. Then this paper mines the frequent-stay points from all stay points by setting threshold. After that, this paper generates a simplified trajectory by using stay point to represent the corresponding interest region. At last, this method uses the Laplace mechanism to add noise to the frequent-stay points. This method realizes trajectory data privacy protection under differential privacy just by adding noise to a part of the locations in a trajectory. The experiment conducted on the real world datasets and simulation datasets shows that the proposed method can improve data utility under the premise of protecting the privacy of trajectory data