A robust malicious user detection scheme in cooperative spectrum sensing

In cognitive radio networks, cooperative spectrum sensing is critical for secondary users to accurately detect primary users. However, it is vulnerable to attacks from malicious users, which intentionally report incorrect sensing results, to mislead other secondary users or the fusion center in decision making. Therefore, detection of malicious users is extremely important for spectrum sensing. This paper proposes a decentralized scheme to detect malicious users in cooperative spectrum sensing. The scheme utilizes spatial correlation of received signal strengths among secondary users in close proximity and is based on robust outlier-detection technique. We have also proposed a neighborhood majority voting approach for the secondary users to decide if a specific user is malicious. Simulation results show that the proposed scheme can achieve a very good performance in detecting malicious users.