Fuzzy Clustering Means (FCM) for Mitigating Spectrum Sensing Data Falsification (SSDF) Attack in Cognitive Radio Networks

Individual sensing was favoured by Collaborative Spectrum sensing (CSS) in Cognitive Radio Network (CRN), since it helps to obtain more accurate sensing decision. In centralized CRN, each node transports its local sensing data to the fusion center build it's the final decision. The Fusion Center decision plays a vital role. Attackers may try to handle the decision-making of the Fusion Center (FC) for selfish rationale or to interfere with the primary user transmission. This paper concentrates on one specific security threat in CRN called Byzantine attack. Also, known as Spectrum sensing data falsification (SSDF) attack. In SSDF attack, harmful users try to control the FC by sending fake sensing report. It plays a vital role in De-centralized network, where the attack resilience has been increased. The mitigation is free-based on fuzzy clustering algorithm. Fuzzy Clustering means (FCM) are proposed to mitigate the malicious user behavior than heretofore existing methods. The proposed approach improves the packet delivery ratio much larger than the preceding methods. The result has been taken in the time of packet transfer from one node to another node. The proposed research has been simulated in the Network Simulator software of Version 3. Robustness of this approach was favoured by simulation results.