Privacy Preserving Serial Publication of Trajectory Data
Md. Muktar Hossain, A.H.M. Sarowar Sattar, Farah Wahida · 2021
Sharing trajectory data with researchers or any organization is very challenging due to individual privacy risk. Specially it becomes more challenging when trajectory data have to share serially after a specific interval. All the existing methods are not applicable for serial publication. Methods for serial publication is required because of dynamic behaviour of trajectory data. In a serial publication of trajectory data, two types of privacy guards must be provided. Firstly, privacy guards is to be used in each release. Secondly, there must be a privacy guard between two releases, so that individual trajectory is not identified. To fulfill these two objectives, we propose a model that consists of space shifting and spatiotemporal points clustering. In our model, two types of clustering approaches have been used. Each cluster meets the concept of k-anonymity that prevent record linkage attack in each release. After applying different clustering algorithm in each release, experimental result shows that our propose approach is able to mitigate intersection attack.