Location Privacy Preservation in Database-Driven Wireless Cognitive Networks Through Encrypted Probabilistic Data Structures

TL;DR

This paper introduces privacy-preserving schemes for database-driven wireless cognitive networks using encrypted probabilistic data structures, enabling spectrum access without revealing user locations.

Contribution

It presents novel location privacy schemes leveraging probabilistic data structures, with two different protocols balancing security, communication, and computational efficiency.

Findings

Schemes guarantee location privacy while querying spectrum databases.

Proposed protocols outperform existing methods in security and efficiency.

Two schemes offer flexible trade-offs between overhead and architectural complexity.

Abstract

In this paper, we propose new location privacy preserving schemes for database-driven cognitive radio networks that protect secondary users' (SUs) location privacy while allowing them to learn spectrum availability in their vicinity. Our schemes harness probabilistic set membership data structures to exploit the structured nature of spectrum databases (DBs) and SUs' queries. This enables us to create a compact representation of DB that could be queried by SUs without having to share their location with DB, thus guaranteeing their location privacy. Our proposed schemes offer different cost-performance characteristics. Our first scheme relies on a simple yet powerful two-party protocol that achieves unconditional security with a plausible communication overhead by making DB send a compacted version of its content to SU which needs only to query this data structure to learn spectrum availability. Our second scheme achieves significantly lower communication and computation overhead for SUs, but requires an additional architectural entity which receives the compacted version of the database and fetches the spectrum availability information in lieu of SUs to alleviate the overhead on the latter. We show that our schemes are secure, and also demonstrate that they offer significant advantages over existing alternatives for various performance and/or security metrics.