Ubiquitous deployment of low-cost mobile positioning devices and the widespread use of high-speed wireless networks has resulted in a huge proliferation of location-based services and location-based data in the big data era. However, the exposure of location information poses significant privacy risks that can invade the location privacy of the users.
Location anonymization refers to the process of perturbing the exact location of users as a spatially and temporally cloaked region such that a user's location becomes indistinguishable from the location of a set of other users.
A fundamental limitation of existing location anonymization techniques is that location information once perturbed to provide a certain anonymity level cannot be reversed to reduce anonymity or the degree of perturbation.
Conventional location anonymization techniques are developed as unidirectional and irreversible techniques which fail to support multi-level access control to location data when data users have different access privileges to the exposed location information.
In this paper, we present ReverseCloak, a new class of reversible spatial and spatio-temporal cloaking mechanisms that effectively provides multi-level location privacy protection, allowing selective de-anonymization of the cloaking region when suitable access credentials are provided. Extensive experiments on real road networks show that our techniques are efficient, scalable and demonstrate good attack resilience.