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iBlock:一种基于智能去中心化区块链的疫情检测与辅助系统。

iBlock: An Intelligent Decentralised Blockchain-based Pandemic Detection and Assisting System.

作者信息

Egala Bhaskara S, Pradhan Ashok K, Badarla Venkataramana, Mohanty Saraju P

机构信息

Department of Computer Science & Engineering, School of Engineering and Applied Science at SRM University, Amaravati, AP India.

Department of Computer Science & Engineering, Indian Institute of Technology (IIT), Tirupati, AP India.

出版信息

J Signal Process Syst. 2022;94(6):595-608. doi: 10.1007/s11265-021-01704-9. Epub 2021 Oct 14.

Abstract

The recent COVID-19 outbreak highlighted the requirement for a more sophisticated healthcare system and real-time data analytics in the pandemic mitigation process. Moreover, real-time data plays a crucial role in the detection and alerting process. Combining smart healthcare systems with accurate real-time information about medical service availability, vaccination, and how the pandemic is spreading can directly affect the quality of life and economy. The existing architecture models are become inadequate in handling the pandemic mitigation process using real-time data. The present models are server-centric and controlled by a single party, where the management of confidentiality, integrity, and availability (CIA) of data is doubtful. Therefore, a decentralised user-centric model is necessary, where the CIA of user data is assured. In this paper, we have suggested a decentralized blockchain-based pandemic detection and assistance system (iBlock). The iBlock uses robust technologies like hybrid computing and IPFS to support system functionality. A pseudo-anonymous personal identity is introduced using H-PCS and cryptography for anonymous data sharing. The distributed data management module guarantees data CIA, security, and privacy using cryptography mechanisms. Furthermore, it delivers useful intelligent information in the form of suggestions and alerts to assist the users. Finally, the iBlock reduces stress on healthcare infrastructure and workers by providing accurate predictions and early warnings using AI/ML.

摘要

近期的新冠疫情凸显了在疫情缓解过程中需要一个更复杂的医疗系统和实时数据分析。此外,实时数据在检测和警报过程中起着至关重要的作用。将智能医疗系统与有关医疗服务可用性、疫苗接种以及疫情传播情况的准确实时信息相结合,会直接影响生活质量和经济。现有的架构模型在使用实时数据处理疫情缓解过程时已变得不足。目前的模型以服务器为中心且由单一方控制,数据的保密性、完整性和可用性(CIA)管理令人怀疑。因此,需要一个以用户为中心的去中心化模型,在该模型中用户数据的CIA能得到保证。在本文中,我们提出了一种基于区块链的去中心化疫情检测与援助系统(iBlock)。iBlock使用混合计算和IPFS等强大技术来支持系统功能。使用H-PCS和密码学引入伪匿名个人身份以进行匿名数据共享。分布式数据管理模块使用加密机制保证数据的CIA、安全性和隐私性。此外,它以建议和警报的形式提供有用的智能信息以协助用户。最后,iBlock通过使用人工智能/机器学习提供准确的预测和早期预警,减轻了医疗基础设施和工作人员的压力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a4f/8515159/9343b8d4c5ac/11265_2021_1704_Fig1_HTML.jpg

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