Optimal Cooperative Detection of Primary User Emulation Attacks in Distributed Cognitive Radio Network

In this paper, we propose a distributed network management algorithm to deal with the detection of primary user emulation (PUE) attacks. For primary users who transmit OFDM signals, with transmit power comparable PUE attackers locating around, we propose a two-phase detection algorithm. It first precisely decides whether the received signal is OFDM signal or not by using autocorrelation algorithm, and then discriminates between PUE attacks and noise based on cooperative energy detection. Afterwards, we prove that energy detection here is a non-linear convex optimization problem. Meanwhile, since secondary users (SUs) may be in the detection range of multiple PUE attacks, the assignment of SUs to detect the PUE attacks is necessary to be considered for achieving optimal system performance. To solve this problem, we introduce the distributed message passing algorithm, which obtains the optimal system detection performance in a computation efficient manner. Finally, simulation results demonstrate that the detection probability of PUE attacks can be greatly improved by virtue of the distributed message passing algorithm. Moreover, comparable improvement is reached by exploring the log-concavity in energy detection.