加强医疗安全:利用区块链技术为保护隐私的 IoMT 传感器监控框架提供基于时间的身份验证

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Aashima Sharma, Sanmeet Kaur, Maninder Singh
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引用次数: 0

摘要

摘要物联网的快速发展及其在医疗保健领域的日益广泛应用,引起了人们对重要医疗数据的保护和隐私问题的极大关注。针对这些问题,区块链作为一种可能的补救措施浮出水面,提供了透明、不可变和去中心化的存储。然而,基于区块链的传统系统在维护匿名性、保密性和隐私性方面仍会遇到限制。因此,本文提出了一个基于安全联盟区块链的框架,该框架优先考虑数据隐私,并采用基于时间的身份验证来简化患者数据监控。首先,我们采用基于时间的身份验证来验证授权用户的身份。这一过程利用 NIK-512 哈希算法与密码和注册时间戳相结合,从而加强了数据的保密性。病人信息在网络内传输前会进行加密。此外,我们的框架还引入了传感器注册服务,由受信任节点为连接到患者的每个传感器分配不同的身份。在边缘层实施数据处理和过滤技术的目的是减轻在收集基于传感器的数据时可能出现的干扰。最后,利用各种指标对性能和安全性进行了全面评估。研究结果表明,所提出的解决方案通过提供更好的隐私和安全性,有效地加强了医疗物联网数据的管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing healthcare security: Time-based authentication for privacy-preserving IoMT sensor monitoring framework leveraging blockchain technology

The rapid progression of the Internet of Things and its increasing use in healthcare has generated considerable concerns over the safeguarding and privacy of vital medical data. In response to these issues, blockchain has surfaced as a possible remedy, offering transparent, immutable, and decentralized storage. Nevertheless, conventional blockchain-based systems still encounter constraints in maintaining anonymity, confidentiality, and privacy. Hence, this article suggests a framework based on a secure consortium blockchain that prioritizes data privacy and employs time-based authentication to streamline patient data monitoring. First, we employ time-based authentication to verify the identities of authorized users. This process utilizes the NIK-512 hashing algorithm in conjunction with passwords and registered timestamps, which strengthens the confidentiality of data. Patient information undergoes encryption before transmission within the network. Further, our framework introduces a sensor registration service that the trusted node employs to assign a distinct identity to each sensor connected to a patient. The implementation of data processing and filtering techniques at the edge layer serves the purpose of mitigating disturbances that may occur during the collection of sensor-based data. Finally, a comprehensive evaluation of performance and security has been carried out with various metrics. The findings indicate that the proposed solution effectively enhances the management of Internet of Medical Things data by providing improved privacy and security.

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来源期刊
Concurrency and Computation-Practice & Experience
Concurrency and Computation-Practice & Experience 工程技术-计算机:理论方法
CiteScore
5.00
自引率
10.00%
发文量
664
审稿时长
9.6 months
期刊介绍: Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.
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