A Flexible Mix-Zone Selection Scheme Towards Trajectory Privacy Protection

The wide application of trajectory analysis research greatly promotes the trajectory dataset publishing which in the meantime carries out tremendous privacy leakage problems, especially those come with long-term pseudonyms. Mix-zone is a typical privacy protection approach in road network that enables a group of users switch to new pseudonyms in certain area. However, to ensure unlinkability between all incoming and all outgoing sub-trajectories, strict restrictions are defined which limits the number of qualified mix-zones. Additionally, the privacy of sub-trajectories is not further considered. In this paper, we propose a flexible trajectory partition scheme called Mix-STC which can find out more candidate mix-zones by means of three-dimensional spatiotemporal cubes calculation. Mix-STC provides privacy protection by limiting the length of sub-trajectories and perturbing the precise location of its end points. Experiments show that Mix-STC performs much better than original data in two different types of de-anonymization attacks. Our performance experiments demonstrate that the datasets processed by Mix-STC can still support typical trajectory applications well.