On Choosing Between Privacy Preservation Mechanisms for Mobile Trajectory Data Sharing.

Various notions of privacy preservation have been proposed for mobile trajectory data sharing/publication. The privacy guarantees provided by these approaches are theoretically very different and cannot be directly compared against each other. They are motivated by different adversary models, making varying assumptions about adversary's background knowledge and intention. A clear comparison between existing mechanisms is missing, making it difficult when a data aggregator/owner needs to pick a mechanism for a given application scenario. We seek to fill this gap by proposing a measure called STRAP that allows comparison of different trajectory privacy mechanisms on a common scale. We also study the trade-off between privacy and utility i.e., how different mechanisms perform when utility constraints are imposed over them. Using STRAP over two real mobile trajectory datasets, we compare state of the art mechanisms for trajectory data privacy and demonstrate the value of the proposed measure.