HTDet: A Clustering Method Using Information Entropy for Hardware Trojan Detection

doi:10.26599/TST.2019.9010047

	HTDet: A Clustering Method Using Information Entropy for Hardware Trojan Detection
	Lu, Renjie 1; Shen, Haihua 1; Feng, Zhihua 2; Li, Huawei 3; Zhao, Wei 1; Li, Xiaowei 3
	2021-02-01
发表期刊	TSINGHUA SCIENCE AND TECHNOLOGY
ISSN	1007-0214
卷号	26 期号:1 页码:48-61
摘要	Hardware Trojans (HTs) have drawn increasing attention in both academia and industry because of their significant potential threat. In this paper, we propose HTDet, a novel HT detection method using information entropy-based clustering. To maintain high concealment, HTs are usually inserted in the regions with low controllability and low observability, which will result in that Trojan logics have extremely low transitions during the simulation. This implies that the regions with the low transitions will provide much more abundant and more important information for HT detection. The HTDet applies information theory technology and a density-based clustering algorithm called Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to detect all suspicious Trojan logics in the circuit under detection. The DBSCAN is an unsupervised learning algorithm, that can improve the applicability of HTDet. In addition, we develop a heuristic test pattern generation method using mutual information to increase the transitions of suspicious Trojan logics. Experiments on circuit benchmarks demonstrate the effectiveness of HTDet.
关键词	Hardware Trojan (HT) detection information entropy Density-Based Spatial Clustering of Applications with Noise (DBSCAN) unsupervised learning clustering mutual information test patterns generation
DOI	10.26599/TST.2019.9010047
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Engineering, Electrical & Electronic
WOS记录号	WOS:000613236900005
出版者	TSINGHUA UNIV PRESS
引用统计	被引频次：22[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/16188
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Shen, Haihua
作者单位	1.Univ Chinese Acad Sci, Beijing 101408, Peoples R China 2.Beijing Inst Comp Technol & Applicat, Beijing 100854, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Lu, Renjie,Shen, Haihua,Feng, Zhihua,et al. HTDet: A Clustering Method Using Information Entropy for Hardware Trojan Detection[J]. TSINGHUA SCIENCE AND TECHNOLOGY,2021,26(1):48-61.
APA	Lu, Renjie,Shen, Haihua,Feng, Zhihua,Li, Huawei,Zhao, Wei,&Li, Xiaowei.(2021).HTDet: A Clustering Method Using Information Entropy for Hardware Trojan Detection.TSINGHUA SCIENCE AND TECHNOLOGY,26(1),48-61.
MLA	Lu, Renjie,et al."HTDet: A Clustering Method Using Information Entropy for Hardware Trojan Detection".TSINGHUA SCIENCE AND TECHNOLOGY 26.1(2021):48-61.