基于改进欧式距离的硬件木马检测

Hardware Trojan Detection Based on Improved Euclidean Distance

传统欧式距离判别方法用于硬件木马检测时,存在判别准确率较低的问题。为此,分析芯片运行时的侧信道功耗信息,根据木马模块触发产生额外功耗的特征,提出一种指数变换改进方案。加入可调参数,以增大硬件木马的可识别度。实验结果表明,与传统欧氏距离判别法相比,参数可调的欧氏距离改进方案可使判别性能提升29%,且木马检测准确率高达98%。

The accuracy of the hardware Trojan detection method based on the traditional Euclidean distance discrimination is too low to meet the demand. For this reason, the side-channel power consumption information is collected and analized in this paper, and an exponential transformation optimization scheme is given based on the extra power consumption caused by the hardware Trojan module. This adjustable parameter is able to increase the recognition of the hardware Trojan. Experimental results show that compared with the traditional Euclidean distance discrimination method, the modified Euclidean distance scheme with adjustable parameters improves the discrimination performance by 29% and the Trojan detection accuracy reaches 98% .