Cuckoo filter-based location-privacy preservation in database-driven cognitive radio networks

Cognitive Radio Networks (CRNs) enable opportunistic access to the licensed channels by allowing secondary users (SUs) to exploit vacant channel opportunities. One effective technique through which SU s acquire whether a channel is vacant is using geo-location databases. Despite their usefulness, geo-location database-driven CRN s suffer from location privacy threats, merely because SUs have to query the database with their exact locations in order to learn about spectrum availability. In this paper, we propose an efficient scheme for database-driven CRN s that preserves the location privacy of SU s while allowing them to learn about available channels in their vicinity. We present a tradeoff between offering an ideal location privacy while having a high communication overhead and compromising some of the users' coordinates at the benefit of incurring much lower overhead. We also study the effectiveness of the proposed scheme under various system parameters.