Secure robust collaborative spectrum sensing in the presence of smart attackers

In this paper, collaborative spectrum sensing to detect random signals corrupted by Gaussian noise in the presence of smart attackers is studied. Unlike to the most of related works, we consider a blind attacker detection so that there is no information about the number of attackers and attack strengths. Also, in our proposed scheme, no information about the Primary User (PU) signal and noise is considered to detect the misbehaved Secondary Users (SUs). In addition, the attack strengths can be chosen differently for each attacker. It is proposed to get assistance from some trusted SUs. We obtain a blind detector and then, a detection algorithm using derived detector to detect the attackers is proposed. Furthermore, in order to evaluate the performance of the proposed detector, the closed form expressions for detection and false alarm probabilities are computed analytically. The provided closed-form analytical results in addition to simulation results show that the proposed detector outperforms significantly the similar secure spectrum sensing schemes.