电子学报 ›› 2017, Vol. 45 ›› Issue (3): 656-661.DOI: 10.3969/j.issn.0372-2112.2017.03.023

• 学术论文 • 上一篇    下一篇

一种基于核最大间距准则的硬件木马检测新方法

李雄伟, 王晓晗, 张阳, 陈开颜, 徐璐   

  1. 军械工程学院信息工程系, 河北石家庄 050003
  • 收稿日期:2015-06-29 修回日期:2016-05-19 出版日期:2017-03-25
    • 作者简介:
    • 李雄伟 男,1975年8月出生,河北定州人,2003年于军械工程学院获得博士学位.现为军械工程学院副教授,主要研究方向为信息安全与对抗.E-mail:lxw-wys@163.com;王晓晗 男,1992年2月出生,河北衡水人,2015年于军械工程学院获得硕士学位.现为军械工程学院博士研究生,主要研究方向为信息安全与对抗.E-mail:wxh2225@126.com
    • 基金资助:
    • 国家自然科学基金 (No.61271152,No.51377170)

A New Hardware Trojan Detection Method Based on Kernel Maximum Margin Criterion

LI Xiong-wei, WANG Xiao-han, ZHANG Yang, CHEN Kai-yan, XU Lu   

  1. Department of Information Engineering, Ordnance Engineering College, Shijiazhuang, Hebei 050003, China
  • Received:2015-06-29 Revised:2016-05-19 Online:2017-03-25 Published:2017-03-25
    • Supported by:
    • National Natural Science Foundation of China (No.61271152, No.51377170)

摘要:

在功耗旁路信号统计模型的基础上,提出了一种基于核最大间距准则的硬件木马检测方法及改进的检测方法.将原始功耗旁路信号映射到高维空间,使其具有更高的可分性,然后再投影到低维子空间,从而发现原始数据中的非线性差异特征,实现功耗旁路信号的非线性特征提取与识别.针对AES加密电路中木马电路的检测实验表明,该方法测得超出检测边界的样本数(792)多于Karhunen-Loève变换(400),取得更好的检测效果.

关键词: 集成电路, 硬件木马, 旁路分析, 核函数, 最大间距准则

Abstract:

A hardware Trojan detection method based on kernel maximum margin criterion and an improved detection method are proposed on basis of the statistical model of power side-channel signal.The methods can map the raw power side-channel signal into a higher dimensional space,where it had a higher separability,and then it is projected onto a low-dimensional subspace,so that non-linear characteristics of differences in the raw data are found,and nonlinear characteristics extraction and recognition of power side-channel signal are achieved.The detection experiment against the Trojan circuit in AES encryption circuit shows that,the number of samples beyond the detection boundary by the method (792) is more than Karhunen-Loève Transform (400),which gets a better detection result.

Key words: integrated circuit, hardware Trojan, side channel analysis, kernel method, maximum margin criterion

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