LMDet: A "Naturalness" Statistical Method for Hardware Trojan Detection | |
Shen, Haihua1,3; Tan, Huazhe1,3; Li, Huawei2; Zhang, Feng4; Li, Xiaowei2 | |
刊名 | IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS
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2018-04-01 | |
卷号 | 26期号:4页码:720-732 |
关键词 | Hardware Trojan (HT) detection natural language processing (NLP) n-gram language model statistical analysis |
ISSN号 | 1063-8210 |
DOI | 10.1109/TVLSI.2017.2781423 |
英文摘要 | 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. |
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 |
语种 | 英语 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
WOS记录号 | WOS:000428615000011 |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.204/handle/2XEOYT63/5751] ![]() |
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.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 3.Beihang Univ, State Key Lab Software Dev Environm, Beijing 100083, 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. |
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