Improving Cooperative Spectrum Sensing in the Presence of Malicious Secondary Users in Cognitive Radio Networks

Accurate spectrum sensing is very important in cognitive radio networks. False sensing results in either waste of spectrum or harmful interference to primary users. To improve accuracy, cooperative spectrum sensing, in which a set of secondary users cooperatively sense the presence of the primary user, has emerged. This technique, however, opens a window for malicious users, who may send false data to the fusion center. This kind of sending false data to the fusion center, which can severely disturb the network, is called spectrum sensing data falsification (SSDF) attacks. In this paper, focusing on stochastic behavior of secondary users and using Expectation-Maximization (EM) algorithm, detection and false alarm probabilities and then the true spectrum state are estimated. Numerical results show improvement in cooperative spectrum sensing operation in respect of common reputation based methods for defending against SSDF attacks. The results also show an increasing in system’s speed and a reduction in communication’s cost.