基于主成分分析和对数几率回归的硬件木马检测  

Hardware Trojan detection based on PCA and logistics regression

作　　者：张金玲[1] 吕蕾[2] ZHANG Jin ling;LU Lei(School of Information,Renmin University of China,Beijing 100872;School of Information Sciences and Engineering,Shandong Normal University,Jinan 250014,China)

机构地区：[1]中国人民大学信息学院,北京100872 [2]山东师范大学信息科学与工程学院,山东济南250014

出　　处：《计算机工程与科学》2018年第7期1187-1191,共5页Computer Engineering & Science

基　　金：国家自然科学基金(61502505)

摘　　要：提出基于主成分分析和对数几率回归的硬件木马检测模型,以提高对硬件木马芯片的检测性能。对采集的旁路功耗信号进行主成分分析组合并选择主要特征,屏蔽信号噪声影响,简化计算操作。利用对数几率回归算法训练分类器,通过计算芯片包含和不包含木马可能性对数比率进行硬件木马识别。设计并搭建FPGA实验平台进行模型验证,通过查准率和查全率评估模型性能。实验结果表明,此模型能够准确高效地检测出硬件木马。We propose a hardware Trojan detection model based on the PCA and logistics regression to promote the detection performance of the IC planted with hardware Trojan.We employ the PCA to analyze the collected side channel power signals and select main features,remove the effect of noise,and simplify the computation.The logistics regression algorithm is adopted to train the classifier.We detect hardware Trojan by calculating the logarithmic ratio between the probability that includes Trojan and the probability that does not include Trojan.An FPGA experiment platform is designed and established to validate the proposed model.Two indicators（precision and recall）are used to evaluate the model＇s performance.Experimental results show that this model can detect hardware Trojan effectively.

关 键 词：硬件木马 旁路信号 主成分分析 对数几率回归 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]