Optimal energy detection in cognitive radio networks in the presence of malicious users

Cognitive radio which is a solution for spectrum scarcity by means of a dynamic spectrum access, imposes some threats to the network. One of these common threats is primary user emulation (PUE) attack, where some malicious users try to mimic the primary signal and deceive secondary users to prevent them from accessing the vacant frequency bands. In this paper, we consider a smart attacker which performs its own spectrum sensing and according to its acquired knowledge about the presence or absent of the primary signal, it optimizes the detection performance in an efficient and implementable way. We derive the optimal voting rule and the optimal number of samples when energy detection is employed. Simulation results show performance improvement is obtained by employing our proposed method compared to naive conventional defense techniques.