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Deterministic and Probabilistic Diagnostic Challenge Generation for Arbiter Physical Unclonable Function

文献类型：期刊论文

作者Ye, Jing1,2; Guo, Qingli1,2; Hu, Yu1,2; Li, Xiaowei1,2
刊名IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
出版日期2018-12-01
卷号37期号:12页码:3186-3197
关键词Arbiter physical unclonable function (PUF) delay fault diagnostic challenge fault diagnosis stuck-at fault
ISSN号0278-0070
DOI10.1109/TCAD.2018.2801224
英文摘要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.
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
语种英语
WOS记录号WOS:000452125300018
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/3524]  
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.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 1000190, 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.

入库方式： OAI收割

来源：计算技术研究所

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