基于HHO-SVM的抗SSDF攻击协作频谱感知方法

doi:10.12305/j.issn.1001-506X.2024.06.33

Abstract

Abstract:

Aiming at the problem of spectrum sensing data falsification (SSDF) attacks in cognitive radio networks, a cooperative spectrum sensing method based on Harris hawks optimization (HHO) algorithm and support vector machine (SVM) for resisting SSDF attacks is proposed. Firstly, feature vectors are extracted from the report information matrix to distinguish the category of secondary users (SU). Secondly, the SVM kernel parameters are optimized with HHO algorithm, and the malicious SU are detected by the optimized SVM model, which improves the accuracy of SU classification in complex sensing environments. Finally, the reliability of SU are calculated according to the optimized SVM model, and the sensing data is fused with credibility as a weight to further strengthen the anti attack capability of the system. Simulation results show that the proposed method can effectively defend against different SSDF attack scenarios, and has better spectrum sensing performance compared with the existing methods.

Key words: spectrum sensing, spectrum sensing data falsification (SSDF) attack, support vector machine (SVM), weighted fusion

CLC Number:

TN92

Quanquan WANG, Zhihao GU, Chengkun WU, Ting WAN. Cooperative spectrum sensing method based on HHO-SVM for resisting SSDF attacks[J]. Systems Engineering and Electronics, 2024, 46(6): 2146-2154.

Figures/Tables 14

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Cooperative spectrum sensing method based on HHO-SVM for resisting SSDF attacks

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