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A novel framework of collaborative early warning for COVID-19 based on blockchain and smart contracts

文献类型：期刊论文

作者Ouyang, Liwei1,2; Yuan, Yong3,4,6; Cao, Yumeng2; Wang, Fei-Yue2,5,6
刊名INFORMATION SCIENCES
出版日期2021-09-01
卷号570页码:124-143
关键词Blockchain Smart contracts Federated learning Learning markets Collaborative early warning
ISSN号0020-0255
DOI10.1016/j.ins.2021.04.021
通讯作者Yuan, Yong(yong.yuan@ia.ac.cn)
英文摘要Early warning is a vital component of emergency response systems for infectious diseases. However, most early warning systems are centralized and isolated, thus there are potential risks of single evidence bias and decision-making errors. In this paper, we tackle this issue via proposing a novel framework of collaborative early warning for COVID-19 based on blockchain and smart contracts, aiming to crowdsource early warning tasks to distributed channels including medical institutions, social organizations, and even individuals. Our framework supports two surveillance modes, namely, medical federation surveillance based on federated learning and social collaboration surveillance based on the learning markets approach, and fuses their monitoring results on emerging cases to alert. By using our framework, medical institutions are expected to obtain better federated surveillance models with privacy protection, and social participants without mutual trusts can also share verified surveillance resources such as data and models, and fuse their surveillance solutions. We implemented our proposed framework based on the Ethereum and IPFS plat-forms. Experimental results show that our framework has advantages of decentralized decision-making, fairness, auditability, and universality. It also has potential guidance and reference value for the early warning and prevention of unknown infectious diseases. (c) 2021 Elsevier Inc. All rights reserved.
WOS关键词DISEASE SURVEILLANCE ; SYSTEMS ; HEALTH ; OUTBREAK ; INTERNET
资助项目National Key R&D Program of China[2018AAA0101401] ; Science and Technology Development Fund, Macau SAR[0050/2020/A1] ; National Natural Science Foundation of China[61533019] ; National Natural Science Foundation of China[71702182]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000659992900008
出版者ELSEVIER SCIENCE INC
资助机构National Key R&D Program of China ; Science and Technology Development Fund, Macau SAR ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/45246]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
通讯作者Yuan, Yong
作者单位1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
3.Renmin Univ China, Sch Math, Beijing 100872, Peoples R China
4.Minist Educ, Engn Res Ctr Finance Computat & Digital Engn, Beijing 100872, Peoples R China
5.Qingdao Acad Intelligent Ind, Qingdao 266109, Peoples R China
6.Macau Univ Sci & Technol, Inst Syst Engn, Macau 999078, Peoples R China
推荐引用方式
GB/T 7714		 Ouyang, Liwei,Yuan, Yong,Cao, Yumeng,et al. A novel framework of collaborative early warning for COVID-19 based on blockchain and smart contracts[J]. INFORMATION SCIENCES,2021,570:124-143.
APA Ouyang, Liwei,Yuan, Yong,Cao, Yumeng,&Wang, Fei-Yue.(2021).A novel framework of collaborative early warning for COVID-19 based on blockchain and smart contracts.INFORMATION SCIENCES,570,124-143.
MLA Ouyang, Liwei,et al."A novel framework of collaborative early warning for COVID-19 based on blockchain and smart contracts".INFORMATION SCIENCES 570(2021):124-143.

入库方式： OAI收割

来源：自动化研究所

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