Secure cooperative spectrum sensing based on Sybil-resilient clustering

The Sybil attack has devastating effect on many distributed decision protocols such as voting: By disguising with multiple identities, a Sybil attacker can amplify his impact on the final outcome. A cooperative spectrum sensing protocol, which aims to enhance the sensing performance over the individual sensing protocols, is a kind of cooperative decision protocol. If not carefully designed, cooperative spectrum sensing can also be very vulnerable to the false-reporting Sybil attack, in which an attacker seeks to degrade the sensing performance by submitting multiple incorrect measurements using multiple identities. In this paper, we exploit the attacker´s limited radio resources and propose a Sybil-resilient clustering mechanism, and adopt it as the basis of a secure cluster-based cooperative sensing protocol. We perform extensive simulation and show that naïve soft data combination and statistics-based false-report-resilient cooperative sensing protocols are susceptible to the Sybil attack; however, our proposed protocol can still provide reasonable sensing outcome despite the presence of Sybil attackers.