Performance Analysis of Cooperative Sensing Based on Reputation Values

In centralized cooperative spectrum sensing, sensing reports from multiple SUs are considered to improve the detection performance of SUs. Fusion center (FC) aggregates these reports and makes a final decision regarding the presence or absence of PU. Malicious SUs will degrade the overall performance of the cognitive radio network. The objective of this work is to detect the malicious users and eliminate them from participating in the decision making process at the FC. The two types of malicious users considered here are namely, primary user emulation attack (PrUEA) and spectrum sensing data falsification (SSDF) attacks. A malleable clustering approach based on the reputation values is proposed to take care of the malicious users. Performance analysis is carried out between hard decision fusion rules with respect to probability of error, packet delivery ratio and transmission delay.