用于检测硬件木马延时的线性判别分析算法

针对芯片生产链长、安全性差、可靠性低，导致硬件木马防不胜防的问题，该文提出一种针对旁路信号分析的木马检测方法。首先采集不同电压下电路的延时信号，通过线性判别分析(LDA)分类算法找出延时差异，若延时与干净电路相同，则判定为干净电路，否则判定有木马。然后联合多项式回归算法对木马延时特征进行拟合，基于回归函数建立木马特征库，最终实现硬件木马的准确识别。实验结果表明，提出的LDA联合线性回归(LR)算法可以根据延时特征识别木马电路，其木马检测率优于其他木马检测方法。更有利的是，随着电路规模的增大意味着数据量的增加，这更便于进行数据分析与特征提取，降低了木马检测难度。通过该方法的研究，对未来工艺极限下识别木马电路、提高芯片安全性与可靠性具有重要的指导作用。

Linear Discriminant Analysis Algorithm for Detecting Hardware Trojans Delay

To solve the security problems of long chip production chain, poor security and low reliability, leading to prevent Hardware Trojan (HT) detection, an HT detection method based on bypass signal analysis is proposed, by means of Linear Discriminant Analysis (LDA) classification algorithm to find the difference in time delay so as to distinguish HT. Then, the polynomial regression algorithm is used to fit the delay feature of the Trojan, and the feature library of the Trojan is established based on the regression function. The experimental results show that the proposed LDA combined with linear regression algorithm can identify HT circuits according to the delay feature, and its HT detection rate is better than other methods. Moreover, it reduces the difficulty of Trojan horse detection as the scale of the circuit increases. Through the research of this method, it has an important guiding role in identifying HT circuits and improving chip security and reliability.