An Eclat Algorithm Based Energy Detection for Cognitive Radio Networks

Abstract

Cognitive radio (CR) can improve the utilization of the spectrum by making use of licensed spectrum in an opportunistic manner. The sensing reports from all the CR nodes are sent to a Fusion Centre (FC) which aggregates these reports and takes decision about the presence of the PU, based on some decision rules. Such a collaborative sensing mechanism forms the foundation of any centralised CRN. However, this collaborative sensing mechanism provides more opportunities for malicious users (MUs) hiding in the legal users to launch spectrum sensing data falsification (SSDF) attacks. In an SSDF attack, some malicious users intentionally report incorrect local sensing results to the FC and disrupt the global decision-making process. To mitigate SSDF attacks, an Eclat algorithm based detection strategy is proposed in this paper for finding out the colluding malicious nodes. Simulation results show that the sensing performance of the scheme is better than the traditional majority based voting decision in the presence of SSDF attacks.