Research On Trajectory Privacy Protection In Data Publishing

In recent years, with the development of mobile communication and sensing technologies, the amount of locations and trajectories of moving objects collected by service providers is continuously increasing. The large scale of trajectories contains wealthy spatio-temporal information, publish the data to the relevant department for data mining purpose will beneficial to multiple applications, bringing revolution to human's living, business pattern and scientific research. But the inherent personal information in the data raises the privacy concern. Therefore, the key challenge is how to wisely use the data without violating each user's location privacy concerns. Design relevant approach to protecting the private information before trajectory publishing becomes research hotspot.In this thesis, we systematically investigate the issues of privacy disclosure in released trajectories, analyze the advantage and disadvantage of existing techniques, and then propose relevant trajectory protection approach to improving the security and data utility of published trajectory.Firstly, for the problem of trajectory k-anonymous, which do not combine the road network, only consider trajectory as a sequence of the coordinates, find the similar trajectory in Euclidean space, result in the underlying risk of privacy disclosure and low data utility. We propose a novel approach to publishing the trajectory data according to road network, which can achieve a high level of security when ensure the usability of publishing trajectory.Secondly, in order to enhance the data utility of published trajectory, we combine the semantics-aware information with the background knowledge of underlying map for the location points and the personal privacy requirements of user, propose a semantic-based approach for privacy-preserving in trajectory publishing, which only deal with those location points located in the sensitive places of user, hence significant improve the data utility when ensure the security.Finally, systematical theoretical and experimental analysis was performed to evaluate the effectiveness of our approach. The result shows that it can achieve a good balance between the security and data utility when implementing our privacy-preserving approach to the trajectories.