基于改进欧式距离的硬件木马检测

发布时间：2018-05-02 12:03

  本文选题：欧式距离判别 + 硬件木马检测　； 参考：《计算机工程》2017年06期

【摘要】：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%。
[Abstract]:When the traditional Euclidean distance discriminant method is used to detect the hardware Trojan horse, it has the problem of low accuracy. This paper analyzes the power consumption information of the side channel when the chip is running, and puts forward an improved scheme of exponential transformation according to the characteristics of extra power generated by the trigger of Trojan horse module. Add adjustable parameters to increase the recognition of hardware Trojans. The experimental results show that, compared with the traditional Euclidean distance discriminant, the improved Euclidean distance with adjustable parameters can improve the discriminant performance by 29%, and the detection accuracy of Trojan horse is as high as 98%.
【作者单位】： 北京电子科技学院电子信息工程系;
【基金】：中央高校基本科研业务费专项资金(2014GCYY04)
【分类号】：TN407
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本文编号：1833808