中圖分類號(hào)：TP309+.1 文獻(xiàn)標(biāo)志碼：A DOI: 10.16157/j.issn.0258-7998.223339 中文引用格式： 李林源，徐金甫，嚴(yán)迎建，等. 基于木馬特征風(fēng)險(xiǎn)敏感的硬件木馬檢測(cè)方法[J]. 電子技術(shù)應(yīng)用，2023，49(6)：35-43. 英文引用格式： Li Linyuan，Xu Jinfu，Yan Yingjian，et al. Hardware Trojan detection method based upon Trojan cost-sensitive[J]. Application of Electronic Technique，2023，49(6)：35-43.
Hardware Trojan detection method based upon Trojan cost-sensitive
Li Linyuan，Xu Jinfu，Yan Yingjian，Liu Yanjiang
(Key Laboratory of Information Security， Information Engineering University， Zhengzhou 450000， China)
Abstract： In the existing hardware Trojan detection methods, there is problem of low detection rate. Therefore, a cost-sensitive hardware Trojan detection was proposed. By analyzing the structural and signal features of Trojan circuits, an 11 dimensional Trojan feature vector was established. A Trojan feature expansion algorithm based on Borderline-SMOTE was proposed, which effectively expanded the Trojan sample information in the training set. Based on PSO algorithm, the parameters of SVM model were optimized, and a cost-sensitive classification model was established. 17 benchmark circuits from the Trust-Hub were used to verify the efficacy of the proposed approach. Among them, the TPR of 16 benchmark circuits is 100%, and the average TNR is as high as 99.04%. Compared with other existing methods, the detection rate of Trojan is improved greatly.
Key words : hardware Trojan detection；cost-sensitive；PSO；SVM classification model
