【Author】
Ouyang, Liwei; Yuan, Yong; Cao, Yumeng; Wang, Fei-Yue
【Source】INFORMATION SCIENCES
【Abstract】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.
【Keywords】Blockchain; Smart contracts; Federated learning; Learning markets; Collaborative early warning
【标题】基于区块链和智能合约的新型 COVID-19 协作预警框架
【摘要】预警是传染病应急响应系统的重要组成部分。然而，大多数预警系统是集中和孤立的，因此存在单证偏倚和决策错误的潜在风险。在本文中，我们通过提出一种基于区块链和智能合约的新型 COVID-19 协作预警框架来解决这个问题，旨在将预警任务众包到包括医疗机构、社会组织甚至个人在内的分布式渠道。我们的框架支持两种监测模式，即基于联邦学习的医疗联合监测和基于学习市场方法的社会协作监测，并将其监测结果融合到新出现的病例上以进行警报。通过使用我们的框架，医疗机构有望获得更好的具有隐私保护的联合监控模型，没有互信的社会参与者也可以共享经过验证的数据和模型等监控资源，并融合他们的监控解决方案。我们基于以太坊和 IPFS 平台实现了我们提出的框架。实验结果表明，我们的框架具有去中心化决策、公平性、可审计性和普遍性等优点。对未知传染病的预警和预防也具有潜在的指导和参考价值。 (c) 2021 Elsevier Inc. 保留所有权利。
【关键词】区块链；智能合约；联邦学习；学习市场；协同预警
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