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

IF 1.6 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Bhaskara S Egala, Ashok K Pradhan, Venkataramana Badarla, Saraju P Mohanty
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引用次数: 0

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.

Abstract Image

Abstract Image

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iBlock:基于区块链的智能去中心化大流行病检测和辅助系统。
最近爆发的 COVID-19 疫情凸显了在大流行病缓解过程中对更先进的医疗保健系统和实时数据分析的需求。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、疫苗接种以及大流行病传播方式的准确实时信息相结合,可直接影响生活和经济质量。现有的架构模型已不足以利用实时数据处理大流行病缓解过程。现有模型以服务器为中心,由单方控制,数据的保密性、完整性和可用性(CIA)管理令人怀疑。因此,有必要建立一个以用户为中心的分散模式,以确保用户数据的保密性、完整性和可用性。在本文中,我们提出了一种基于区块链的去中心化大流行病检测和援助系统(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 和密码学引入了一个伪匿名个人身份,用于匿名数据共享。分布式数据管理模块利用加密机制保证数据的 CIA、安全性和隐私性。此外,它还以建议和警报的形式提供有用的智能信息,为用户提供帮助。最后,iBlock 利用人工智能/ML 提供准确的预测和预警,减轻了医疗基础设施和工作人员的压力。
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来源期刊
CiteScore
4.00
自引率
0.00%
发文量
106
审稿时长
4-8 weeks
期刊介绍: The Journal of Signal Processing Systems for Signal, Image, and Video Technology publishes research papers on the design and implementation of signal processing systems, with or without VLSI circuits. The journal is published in twelve issues and is distributed to engineers, researchers, and educators in the general field of signal processing systems.
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