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基于旁路分析的硬件木马检测方法
引用本文:王力纬,罗宏伟,姚若河.基于旁路分析的硬件木马检测方法[J].华南理工大学学报(自然科学版),2012,40(6):6-10.
作者姓名:王力纬  罗宏伟  姚若河
作者单位:1. 华南理工大学电子与信息学院,广东广州510640;工业和信息化部电子第五研究所电子元器件可靠性物理及其应用技术重点实验室,广东广州510610
2. 工业和信息化部电子第五研究所电子元器件可靠性物理及其应用技术重点实验室,广东广州,510610
3. 华南理工大学电子与信息学院,广东广州,510640
基金项目:总装备部预研项目,总装备部元器件共性课题
摘    要:集成电路芯片在不受控的制造过程中可能会被嵌入恶意电路结构,形成硬件木马,这给集成电路芯片的可靠性和可信度带来了极大的隐患,而利用传统的测试技术很难发现这些硬件木马.针对这一问题,文中提出了一种非破坏性的、基于旁路分析的硬件木马检测方法,它通过对芯片功耗瞬态变化情况的分析,采用奇异值分解算法对功耗进行统计处理来检测芯片中的硬件木马.在FPGA芯片上的硬件验证结果表明,即使在测量噪声和工艺扰动较大的环境中,文中方法也能检测出面积比原始电路小2个数量级的硬件木马.

关 键 词:硬件木马  旁路分析  奇异值分解

Side-Channel Analysis-Based Detection Approach of Hardware Trojans
Wang Li-wei , Luo Hong-wei , Yao Ruo-he.Side-Channel Analysis-Based Detection Approach of Hardware Trojans[J].Journal of South China University of Technology(Natural Science Edition),2012,40(6):6-10.
Authors:Wang Li-wei  Luo Hong-wei  Yao Ruo-he
Institution:1(1.School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China; 2.Science and Technology on Reliability Physics and Application of Electronic Component Laboratory,The Fifth Electronics Research Institute of the Ministry of Industry and Information Technology,Guangzhou 510610,Guangdong,China)
Abstract:During the fabrication of integrated circuit(IC) chips in untrusted foundries,malicious circuits may be inserted as hardware Trojans,which results in a significant risk of trustworthiness and reliability degradation of the chips.As such Trojan circuits are difficult to detect using conventional strategies,a nondestructive side-channel analysis-based detection approach is proposed,which employs the algorithm of singular value decomposition to analyze and statistically process the transient power of IC chips.Validation results of the approach on FPGA chips show that,even in the presence of big noise and process variation,the proposed approach is effective in detecting the hardware Trojans that are 2 orders of magnitude smaller than the original circuit.
Keywords:hardware Trojans  side-channel analysis  singular value decomposition
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