Sky caching assisted k-anonymity in spatial querying

As smartphones are prevalent and resource-rich, users can freely query any point-of-interest (POI) and enjoy diverse location-based services (LBS) deployed in infrastructure-based wireless networks. However, users often trade their location privacy with services by sharing their location information with a LBS server, without knowing whether the server can be trusted. In this thesis, we propose a privacy-aware spatial query scheme and its corresponding operations with the support of a flying drone. The basic idea is that both user and its drone conduct a query operation collaboratively using an extended k-anonymity. We also propose cache admission control schemes to efficiently cache the queried results into the storage of user and/or drone. Since both caches of user and drone can virtually form an aggregate cache, a decision as to whether to cache the queried results depends not only on the user itself, but also on the drone. The location privacy of user is analyzed and measured in terms of cache hit and size of convex-hull, consisting of dummy locations resided within the cloaking areas of user and drone. We conduct extensive simulation experiments using the OMNeT++ for performance evaluation and comparison. The simulation results show that the proposed drone-assisted approach can improve location obfuscation and extend cloaking area significantly.