FeCrypto: Instruction Set Architecture for Cryptographic Algorithms Based on FeFET-Based In-Memory Computing

doi:10.1109/TCAD.2022.3233736

	FeCrypto: Instruction Set Architecture for Cryptographic Algorithms Based on FeFET-Based In-Memory Computing
	Liu, Rui 1,2; Zhang, Xiaoyu 2,3; Xie, Zhiwen 2,3; Wang, Xinyu 2,3; Li, Zerun 2,3; Chen, Xiaoming 2,3; Han, Yinhe 2,3; Tang, Minghua 1
	2023-09-01
发表期刊	IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
ISSN	0278-0070
卷号	42 期号:9 页码:2889-2902
摘要	often achieved by artificially adding noise, near-term quantum Recently, computers are inherently noisy and it was observed that this leads to natural differential privacy as a feature. In this work we discuss quantum differential privacy in an information theoretic framework by casting it as a quantum divergence. A main advantage of this approach is that differential privacy becomes a property solely based on the output states of the computation, without the need to check it for every measurement. This leads to simpler proofs and generalized statements of its properties as well as several new bounds for both, general and specific, noise models. In particular, these include common representations of quantum circuits and quantum machine learning concepts. Here, we focus on the difference in the amount of noise required to achieve certain levels of differential privacy versus the amount that would make any computation useless. Finally, we also generalize the classical concepts of local differential privacy, R & eacute;nyi differential privacy and the hypothesis testing interpretation to the quantum setting, providing several new properties and insights. Index Terms- Quantum computing, quantum information science, data privacy, differential privacy.
关键词	Computing-in-memory (CiM) cryptographic algorithm ferroelectric field-effect transistor (FeFET) instruc-tion set architecture (ISA)
DOI	10.1109/TCAD.2022.3233736
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2018YFA0701500] ; National Natural Science Foundation of China[62122076] ; National Natural Science Foundation of China[61834006] ; National Natural Science Foundation of China[62025404] ; National Natural Science Foundation of China[92164108] ; National Natural Science Foundation of China[11835008] ; Key Research Program of Frontier Sciences, Chinese Academy of Sciences[ZDBS-LY-JSC012] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB44000000] ; Foundation of Innovation Center of Radiation Application[KFZC2020020901] ; Youth Innovation Promotion Association CAS ; Innovative Project of Institute of Computing Technology, Chinese Academy of Sciences[E261040]
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:001059125400010
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：1[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/2XEOYT63/21158
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Chen, Xiaoming; Tang, Minghua
作者单位	1.Xiangtan Univ, Sch Mat Sci & Engn, Hunan 411105, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Liu, Rui,Zhang, Xiaoyu,Xie, Zhiwen,et al. FeCrypto: Instruction Set Architecture for Cryptographic Algorithms Based on FeFET-Based In-Memory Computing[J]. IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS,2023,42(9):2889-2902.
APA	Liu, Rui.,Zhang, Xiaoyu.,Xie, Zhiwen.,Wang, Xinyu.,Li, Zerun.,...&Tang, Minghua.(2023).FeCrypto: Instruction Set Architecture for Cryptographic Algorithms Based on FeFET-Based In-Memory Computing.IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS,42(9),2889-2902.
MLA	Liu, Rui,et al."FeCrypto: Instruction Set Architecture for Cryptographic Algorithms Based on FeFET-Based In-Memory Computing".IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 42.9(2023):2889-2902.