Dynamic Threshold Selection Approach in Voting Rule for Detection of Primary User Emulation Attack

DOI : 10.5152/iujeee.2018.1819 Cognitive Radio (CR) technology presents a mechanism for efficient spectrum usage. Spectrum sensing is an essential function of CR which includes an intelligent signal processing algorithm to identify the spectrum holes. Cooperative Spectrum Sensing (CSS) has been widely adopted to improve the performance of the CR networks. Unfortunately, it is vulnerable to security attacks. In this study, we propose an optimal threshold selection approach to address one of the important kinds of attacks called Primary User Emulation Attack (PUEA).  In PUEA, a malicious attacker mimics primary signal characteristics and deceive the CR users to avoid them from detecting spectrum holes. We assume a malicious PUEA which is relatively located the near of the PU and perform spectrum sensing and exactly detect the vacant frequency bands to transmit its fake signal. The idea is based on attack strength estimation, where the attack strength is defined as the ratio of the average received SNR of the attacker to the received SNR of PU. The obtained attack strength is innovatively applied in K-out-N rule to obtain an optimum and dynamic value of K that minimizes the global error probability. The results indicate that the proposed method has higher performance in detecting the malicious PUEA comparing with the conventional methods.