认知无线电网络中安全的协作频谱检测算法

在认知无线电网络中,当认知用户存在虚假感知信息SSDF时,协作频谱感知的性能会受到巨大影响。为了确保频谱感知的鲁棒性,提出了一种基于信誉度加权序贯频谱检测算法来识别恶意用户并减轻他们造成的影响。该算法通过使用认知用户的近期感知信息计算本地信誉度函数,再综合考虑其信誉值与感知过程中表现的稳定程度以消除恶意用户对主用户的传输效率带来的影响。仿真结果表明,在恶意攻击环境下,新算法优于现有典型协作频谱感知算法。

A secure cooperative spectrum detection algorithm in cognitive radio networks

The performance of cooperative spectrum sensing can be affected tremendously when there are spectrum sensing data falsification (SSDF) attacks in cognitive radio networks. To ensure the robustness of spectrum sensing, we propose a sequential spectrum sensing algorithm in this paper based on the credibility of the weighted sequential spectrum to identify misbehaviors and mitigate their harmful influence on sensing performance. We calculate the local reputation function by using recent sensing information of the cognitive user. Then the credibility value and the stability in the sensing process work jointly to eliminate the impact of malicious users on transmission efficiency. Simulation results show that the new algorithm outperforms the typical cooperative spectrum sensing algorithm in malicious environment.