LMDet: A "Naturalness" Statistical Method for Hardware Trojan Detection

doi:10.1109/TVLSI.2017.2781423

	LMDet: A "Naturalness" Statistical Method for Hardware Trojan Detection
	Shen, Haihua 1,2; Tan, Huazhe 1,2; Li, Huawei 3; Zhang, Feng 4; Li, Xiaowei 3
	2018-04-01
发表期刊	IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS
ISSN	1063-8210
卷号	26 期号:4 页码:720-732
摘要	Hardware Trojans (HTs) are emerging threats for integrated circuits. In this paper, we propose a novel scheme, named LMDet, to detect HTs through distinguishing the "unnaturalness" of HTs from the "naturalness" of normal circuits using the natural language processing technology. The key insight of LMDet is that we find clean circuits tend to be "natural" (i.e., to be highly repetitive in structure) and HTs appear to be "unnatural" (i.e., to be rare in structure) in some sense. LMDet models circuit gates sequentially, using the n-gram language model. Gate sequences from the circuit under detection (CUD) are assessed according to their probability in the model, and low-probability sequences are marked as suspected Trojan-related gates. Evaluation with benchmarks and industrial circuits shows that LMDet is capable of detecting Trojan logic without the HT-free reference of CUD. LMDet has short execution time on large commercial circuits with acceptable space overhead. It is a promising method in real industry since plenty of HT-free designs are available as training corpus to ensure good statistical effects.
关键词	Hardware Trojan (HT) detection natural language processing (NLP) n-gram language model statistical analysis
DOI	10.1109/TVLSI.2017.2781423
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61432017] ; National Natural Science Foundation of China[61474134] ; National Natural Science Foundation of China[61532017] ; National Key Research and Development Program of China[2016YFF0203500]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Hardware & Architecture ; Engineering, Electrical & Electronic
WOS记录号	WOS:000428615000011
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：12[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/2XEOYT63/5752
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; Li, Huawei
作者单位	1.Univ Chinese Acad Sci, Beijing 100190, Peoples R China 2.Beihang Univ, State Key Lab Software Dev Environm, Beijing 100083, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 4.Chinese Acad Sci, Inst Microelect, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Shen, Haihua,Tan, Huazhe,Li, Huawei,et al. LMDet: A "Naturalness" Statistical Method for Hardware Trojan Detection[J]. IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS,2018,26(4):720-732.
APA	Shen, Haihua,Tan, Huazhe,Li, Huawei,Zhang, Feng,&Li, Xiaowei.(2018).LMDet: A "Naturalness" Statistical Method for Hardware Trojan Detection.IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS,26(4),720-732.
MLA	Shen, Haihua,et al."LMDet: A "Naturalness" Statistical Method for Hardware Trojan Detection".IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 26.4(2018):720-732.