CASIA OpenIR  > 多模态人工智能系统全国重点实验室
Asynchronous Threshold ECDSA With Batch Processing
Zhang, Hongxin1; Xie, Guanghuan1; Zou, Xin1; Zhang, Chi1; Li, Zhuo2; Qin, Rui3; Xiong, Gang3; Wang, Fei-Yue4,5,6
Source PublicationIEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
ISSN2329-924X
2023-01-09
Pages10
Corresponding AuthorLi, Zhuo(lizhuo@zju.edu.cn)
AbstractThreshold Elliptic Curve Digital Signature Algorithm (ECDSA) has attracted a lot of attention due to the wide applications of ECDSA in crypto asset. Although several variants of threshold signature protocols can provide functions, such as key generation and signing, they suffer from two shortfalls. First, these schemes only discuss a single signature computation task in a synchronous algorithm context, which is difficult to adapt to real crypto-asset applications, such as custody. Second, these schemes are computing intensive and not scalable, hence can hardly support large-scale processing operations in real life even after traditional optimization, such as multithreading, is applied. In this article, we propose an innovative computation method called asynchronous threshold ECDSA with batch processing, based on the interactive threshold signature protocols. The method provides a reliable solution for critical operational scenarios, such as threshold signing and distributed key generation (DKG) in crypto-asset custody, and can be a future reference in secure data distribution mechanisms. The performance and scalability of our methods are validated through a benchmark testing.
KeywordProtocols Peer-to-peer computing Batch production systems Digital signatures Blockchains Electronic mail Urban areas Blockchain crypto-asset custody secure multiparty computation (MPC) threshold signature
DOI10.1109/TCSS.2022.3230903
Indexed BySCI
Language英语
Funding ProjectScience and Technology Development Fund of Macau SAR[0050/2020/A1]
Funding OrganizationScience and Technology Development Fund of Macau SAR
WOS Research AreaComputer Science
WOS SubjectComputer Science, Cybernetics ; Computer Science, Information Systems
WOS IDWOS:000920538500001
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/51429
Collection多模态人工智能系统全国重点实验室
Corresponding AuthorLi, Zhuo
Affiliation1.Zhejiang Univ, State Key Lab CAD & CG, Hangzhou 310058, Peoples R China
2.State St Technol Zhejiang Ltd, Global Technol Serv Dept, Hangzhou 310000, Peoples R China
3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
6.Macau Univ Sci & Technol, Macao Inst Syst Engn, Macau 999078, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Hongxin,Xie, Guanghuan,Zou, Xin,et al. Asynchronous Threshold ECDSA With Batch Processing[J]. IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,2023:10.
APA Zhang, Hongxin.,Xie, Guanghuan.,Zou, Xin.,Zhang, Chi.,Li, Zhuo.,...&Wang, Fei-Yue.(2023).Asynchronous Threshold ECDSA With Batch Processing.IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,10.
MLA Zhang, Hongxin,et al."Asynchronous Threshold ECDSA With Batch Processing".IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS (2023):10.
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