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Compressed spectrum sensing defensive against wideband SSDF attacks
宽带SSDF攻击下的压缩频谱感知

Keywords: cognitive radio,wideband spectrum sensing,wideband spectrum sensing data falsification(wideband SSDF),compressed sampling,average consensus
认知无线电
,宽带频谱感知,宽带SSDF攻击,压缩采样,平均一致算法

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Abstract:

This paper proposes a new SSDF attacking model called Wideband SSDF Attack, and on the basis that the wireless signal in cognitive radio network is inherently sparse in frequency domain, this paper develops a distributed compressed wideband spectrum sensing approach which combines compressed sensing and average consensus algorithm to defend against such wideband SSDF attacks. Spectrum sensing takes two stages: sensing stage and fusion stage. At sensing stage, compressed sensing is performed at each CR node to sample the received time domain wideband primary user signal at practical complexity and cost, and then each CR node locally reconstructs the frequency domain signal. At fusion stage, to defend against wideband SSDF attacks, we evaluate reputation values for each subchanel, and then the local spectrum sensing results of each CR are fused and then we can exclude the influence of potential malicious node at the same time without a fusion center at each subchanel. Simulation results show that the proposed spectrum sensing scheme can defend against wideband SSDF attacks, and spectrum sensing performance is enhanced and at the same time we get extra diversity gain by exploiting useful information from malicious node using our proposed model.

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