Optimal Geo-Indistinguishable Mechanisms for Location Privacy
This work addresses privacy-utility optimization for location-based services, offering incremental improvements in computational efficiency.
The paper tackles the trade-off between geo-indistinguishability and utility in location privacy by constructing a mechanism that minimizes service quality loss using linear programming, and reduces constraints from cubic to quadratic to speed up computation and handle larger location sets.
We consider the geo-indistinguishability approach to location privacy, and the trade-off with respect to utility. We show that, given a desired degree of geo-indistinguishability, it is possible to construct a mechanism that minimizes the service quality loss, using linear programming techniques. In addition we show that, under certain conditions, such mechanism also provides optimal privacy in the sense of Shokri et al. Furthermore, we propose a method to reduce the number of constraints of the linear program from cubic to quadratic, maintaining the privacy guarantees and without affecting significantly the utility of the generated mechanism. This reduces considerably the time required to solve the linear program, thus enlarging significantly the location sets for which the optimal mechanisms can be computed.