Privacy-preserving spatiotemporal matching

The explosive growth of mobile-connected and location-aware devices makes it possible to have a new way of establishing trust relationships, which we coin as spatiotemporal matching. In particular, a mobile user could very easily maintain his spatiotemporal profile recording his continuous whereabouts in time, and the level of his spatiotemporal profile matching that of the other user can be translated into the level of trust they two can have in each other. Since spatiotemporal profiles contain very sensitive personal information, privacy-preserving spatiotemporal matching is needed to ensure that as little information as possible about the spatiotemporal profile of either matching participant is disclosed beyond the matching result. We propose a cryptographic solution based on Private Set Intersection Cardinality and a more efficient non-cryptographic solution involving a novel use of the Bloom filter. We thoroughly analyze both solutions and compare their efficacy and efficiency via detailed simulation studies.