Secure Collaborative Spectrum Sensing in the Presence of Primary User Emulation Attack in Cognitive Radio Networks

Abstract

Collaborative Spectrum Sensing (CSS) is an effective approach to improve the detection performance in Cognitive Radio (CR) networks. Inherent characteristics of the CR have imposed some additional security threats to the networks. One of the common threats is Primary User Emulation Attack (PUEA). In PUEA, some malicious users try to imitate primary signal characteristics and defraud the CR users to prevent them from accessing the idle frequency bands. The present study investigates a new CSS scheme in the presence of a smart PUEA, which is aware of idle frequency channels and transmits its fake signal in a way that CR users are not easily able to discriminate between the received signal from the PU and PUEA. The idea is based on the Bayes risk criterion. More precisely, the sensing results of the CR users are summed up in the Fusion Center (FC) and compared with the optimum threshold that minimizes the Bayes risk. We also discuss practical limitation issue that need to be considered when applying the proposed method. Simulation results are provided to indicate the superiority of the proposed method against PUEA compared with conventional method.