Performance Improvements of Reputation-Based Cooperative Spectrum Sensing

Cognitive radio is establishing itself as the most promising technology in tackling the problem of spectrum scarcity. It allows secondary users to opportunistically access and re-use the spectrum resources under-utilized by licensed or primary users. Spectrum sensing (either cooperative or noncooperative modes) is exploited to identify those unused (free) frequency bands. This new technology has been proved to be vulnerable to an increasing number of attacks, such as Byzantine attacks. Here, we propose a novel reputation-based cooperative spectrum sensing method that first detects, and then rejects any malicious secondary user, thus improving the system performances. We evaluate the error probabilities (detection vs. false alarms) of the system, as well as the number of both correctly identified attackers and discarded honest users. Finally, we compare our method to a recently published reputation-based method (either blind or non-blind). As shown by the simulation results, the proposed method outperforms the conventional approach, confirming its robustness in detecting different types of Byzantine attacks.