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 naive 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.