A Punishment Policy for Spectrum Sensing Data Falsification Attackers in Cognitive Radio Networks

Cooperative Spectrum Sensing (CSS) was envisioned to improve the reliability of spectrum sensing process in cognitive radio networks. However, CSS is prone to security threats that degrade the overall performance. A popular attack in CSS is called spectrum sensing data falsification (SSDF) attack. In SSDF attack, a malicious user sends false spectrum sensing results to the fusion center, which significantly degrades detection accuracy and energy efficiency. In this paper, an attacker-punishment policy is proposed. The proposed policy is based on relating the scheduling probability for each user to its sensing performance, representing a punishment for attackers and a reward for honest users. The proposed policy includes identifying attackers, ignoring their reported results, and assigning a proper scheduling probability to each user. Two different approaches are presented to accomplish the proposed policy, namely, Majority-based Assessment and Delivery-based Assessment. Simulation results show that the proposed policy improves the individual energy efficiency of the honest CUs, and degrades the energy efficiency of the attackers.