Cooperative spectrum sensing algorithm based on bilateral threshold selection against Byzantine attack

基于双边阈值的抗Byzantine攻击协作频谱感知算法（英文）

To deal with Byzantine attacks in 5 G cognitive radio networks,a bilateral threshold selection-based algorithm is proposed in the spectrum sensing process. In each round,secondary uses( SUs) first submit the energy values and instantaneous detection signal-to-noise ratios( SNRs) to the fusion center( FC). According to detection SNRs,the FC conducts normalization calculations on the energy values. Then,the FC makes a sort operation for these normalized energy values and traverses all the possible mid-points between these sorted normalized energy values to maximize the classification accuracy of each SU. Finally,by introducing the recognition probability and misclassification probability,the distributions of the normalized energy values are analyzed and the bilateral threshold of classification accuracy is obtained via a target misclassification probability. Hence,the blacklist of malicious secondary users( MSUs) is obtained. Simulation results show that the proposed scheme outperforms the current mainstream schemes in correct sensing probability,false alarm probability and detection probability.

为了解决5G认知无线网络中的Byzantine攻击,在频谱感知过程中提出了一种双边阈值筛选方案.在每个回合中,从用户首先将感知能量值和检测信噪比提交给融合中心.根据检测信噪比,融合中心对能量值进行归一化.然后,对归一化能量值进行排序并遍历这些归一化能量值的中点,以最大化从用户的分类准确率.此外,通过引入识别概率和误筛概率,分析了归一化能量值的分布,从而推导了给定误筛概率情况下的恶意用户双边筛选阈值.最后,通过该双边筛选阈值获得恶意用户名单.仿真结果表明:所提方案的主用户正确感知率、虚警和检测概率均要优于当前主流方案.