Deterministic and Probabilistic Diagnostic Challenge Generation for Arbiter Physical Unclonable Function | |
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 |
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 |
DOI | 10.1109/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 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
WOS记录号 | WOS:000452125300018 |
内容类型 | 期刊论文 |
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. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论