A similarity algorithm based on hamming distance used to detect malicious users in cooperative spectrum sensing

摘要

The collaborative spectrum sensing (CSS) methods have been proposed to improve the sensing performance. However, rare studies take security into account. The collaborative spectrum sensing (CSS) is vulnerable to the potential attacks from malicious users (MUs). Most existing MU detection methods are reputation-based, it is incapable as the attack model is intelligent. In this paper, a hamming distance check (HDC) is proposed to detect MUs. The hamming distance between all the sensing nodes is calculated. For the reports from MUs is different from honest users (HUs), we can find the MUs and exclude in the fusion process. A new trust factor (TF) is proposed to increase the effects of trustworthy nodes in the final decision. The proposed algorithm can effectively detect the MUs without prior knowledge. In addition, our proposed method can perform better than the existing approaches.