Deterministic and Probabilistic Diagnostic Challenge Generation for Arbiter Physical Unclonable Function

doi:10.1109/TCAD.2018.2801224

	Deterministic and Probabilistic Diagnostic Challenge Generation for Arbiter Physical Unclonable Function
	Ye, Jing 1,2; Guo, Qingli 1,2; Hu, Yu 1,2; Li, Xiaowei 1,2
	2018-12-01
发表期刊	IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
ISSN	0278-0070
卷号	37 期号:12 页码:3186-3197
摘要	Physical unclonable functions (PUFs) have broad application prospects in the field of hardware security. Like faults in general-purpose circuits, faults may also occur in PUFs. Fault diagnosis plays an important role in the yield learning process. Traditional fault diagnosis methods are based on comparing the fault-free responses of a design and the failing responses of chips. However, different manufactured, fault-free PUFs with the same design have different challenge-response pairs, so PUFs do not have deterministic, fault-free responses. Hence, traditional fault diagnosis methods are unsuitable for PUFs. To effectively diagnose PUFs, this paper proposes a diagnostic challenge generation method for the typical PUF: arbiter PUF. The diagnostic challenges that can deterministically or probabilistically distinguish the suspect faults of arbiter PUFs are generated. Simulation experiments on diagnosing failing arbiter PUF instances show that all the actual fault locations are accurately included in the candidate sets, and the average number of candidate locations (i.e., diagnostic resolution) is 1.585. FPGA experiments on diagnosing real PUFs show that the diagnostic accuracy is also 1, and the average diagnostic resolution is 1.602.
关键词	Arbiter physical unclonable function (PUF) delay fault diagnostic challenge fault diagnosis stuck-at fault
DOI	10.1109/TCAD.2018.2801224
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61532017] ; National Natural Science Foundation of China[61704174] ; National Natural Science Foundation of China[61432017] ; National Natural Science Foundation of China[61376043] ; National Natural Science Foundation of China[61521092]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Interdisciplinary Applications ; Engineering, Electrical & Electronic
WOS记录号	WOS:000452125300018
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：3[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/2XEOYT63/3525
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Hu, Yu; Li, Xiaowei
作者单位	1.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 1000190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Ye, Jing,Guo, Qingli,Hu, Yu,et al. Deterministic and Probabilistic Diagnostic Challenge Generation for Arbiter Physical Unclonable Function[J]. IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS,2018,37(12):3186-3197.
APA	Ye, Jing,Guo, Qingli,Hu, Yu,&Li, Xiaowei.(2018).Deterministic and Probabilistic Diagnostic Challenge Generation for Arbiter Physical Unclonable Function.IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS,37(12),3186-3197.
MLA	Ye, Jing,et al."Deterministic and Probabilistic Diagnostic Challenge Generation for Arbiter Physical Unclonable Function".IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 37.12(2018):3186-3197.