Efficient Byzantine Defense Algorithm for Cooperative Spectrum Sensing in Cognitive Radio Networks

Abstract

Cooperative spectrum sensing (CSS) is a process of achieving spatial diversity gain to make global decision for cognitive radio networks (CRNs). However, the accuracy of the global decision effects owing to the presence of Byzantine during cooperative sensing, therefore causing severe performance degradation of CSS. In front of malicious users (MUs) launching Byzantine attack, a robust defense framework is proposed to defend against Byzantine attack and improve the efficiency of the CSS. For this aim, a novelty weighted single symbol (WSS) algorithm based on the reputation value update mechanism and the single symbol report method is proposed in this paper. We first propose a defense framework based on the reputation value distribution. In order to ensure the accuracy of Byzantine identification, we further evaluate the reputation value of secondary users (SUs)’ reports by mean of data transmission consistency verification. Moreover, the single symbol report method is utilized to improve the efficiency of Byzantine defense algorithm and reduce the report sample size. Finally, a series of mathematical analyses prove that the proposed defense framework improves the efficiency of CSS under Byzantine attacks.