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Robust and efficient cooperative spectrum sensing against probabilistic hard Byzantine attack

Cognitive radio (CR) is regarded as a powerful technology to solve the problem of spectrum shortage and underutilization. As a key function of CR technology, cooperative spectrum sensing (CSS) allows secondary users (SUs) to detect the primary user (PU)'s signal so that they identify and opportunistically access the available spectrum. However, the openness of CSS paradigm makes cognitive radio networks (CRNs) suffer from Byzantine attack, thereby undermining the premise of CR framework. To this aim, we formulate a probabilistic hard Byzantine attack model, in which malicious users (MUs) can conduct various attack strategies, and make an in‐depth investigation on the blind scenario. On the one hand, in order to ensure the robustness of CSS, a method to evaluate the reliability of the secondary user (SU)'s sensing result based on the channel status detection is proposed and an innovative weight coefficient is considered to selectively utilize the sensing information from MUs. On the other hand, we design a sequential fusion method based on reputation value (RV) and differential mechanism, with the aim of improving the efficiency of CSS. According to above methods and mechanism, the weighted differential sequential symbol (WDS2) algorithm is designed, which integrates the weight evaluation into sequential method to make the global decision for CSS. Finally, compared to the existing various data fusion algorithms, simulation results show that the proposed WDS2 not only defends against various Byzantine attacks to secure the robustness of CSS, but also requires less samples in support of an accurate global decision to improve the efficiency of CSS.