基于区块链技术构建物联网医疗领域基于动态排列的隐私保护模型

A. Yogeshwar, S. Kamalakkannan
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引用次数: 1

摘要

区块链技术有可能通过建立一种技术标准来解决卫生信息系统中目前的互操作性问题,该技术标准可确保人们、医疗保健供应商和包括医疗专业人员在内的医疗维护组织之间安全的电子卫生数据交换。患者的感官数据可以实时输入到物联网(IoT)设备中,这些设备可以在医疗保健行业中进行评估和管理。与患者有关的健康数据的隐私和安全现在也是各种产品领域的物联网设备的主要关注点。根据之前的研究,区块链技术已被确定为解决物联网中存在的数据安全问题的重要答案。本文提出了一种基于多模态安全数据(DPMMSD)动态排列的超椭圆曲线加密(HECC)框架(DPMMSD-HECC),用于物联网中患者数据的安全接收和监管。建议的物联网设备中医疗保健数据管理框架成功地用于满足最佳的机密性和安全性要求。本研究使用区块链方法来开发一个可靠和安全的数据共享平台,该平台连接多个信息源,并在分布式账本中加密和记录物联网数据。一项关于安全性的研究表明,特定的信息为数据分析人员提供了与DPMMSD-HECC模型相关的参数的安全性,并维护了来自每个数据源的重要数据的保密性。将推荐的策略与来自UCI AI存储库的两个基准数据集进行比较:乳腺癌威斯康星州数据集(BCWD)和心脏病数据集(HDD)。的。仿真结果表明,所提出的DPMMSD-HECC模型在许多方面都优于所有其他技术。
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Building Dynamic permutation based Privacy Preservation Model with Block Chain Technology for IoT Healthcare Sector
Blockchain technology has the potential to address present interoperability issues in health information systems by establishing a technological standard that ensures safe electronic health data exchange amongst people, healthcare suppliers and medicinal up keep organizations including medical professionals. Patients' sensory data can be fed into Internet of Things (IoT) devices in real timewhich can be evaluated and managed in the healthcare industry. The privacy and security of health data pertaining topatients' is now also a major concern with IoT devices across a wide variety of product sectors. According to previous research, blockchain technology has been determined to be a substantial answer to the data security concerns that present in IoT. The Dynamic Permutation with Multi-Modal Safe Data (DPMMSD) based Hyper Elliptic Curve Cryptography (HECC) Framework (DPMMSD-HECC) is suggested in this research for safeadmission and regulator topatient's data in IoT. The suggested framework of healthcare data management in IoT devices is successfully utilized for fulfilling the optimum confidentiality and safety requirements. Blockchain approach has beenused in this study to develop a dependable and safe data sharing stage that connects several information sources and encrypts and records IoT data in a distributed ledger. A research on security revealed that a particular information secures the parameters related to DPMMSD-HECC model for data analysts and maintains the secrecy of important data from each data source. The recommended strategy is evaluated compared to two benchmark datasets from the UCI AI repository: Breast Cancer Wisconsin Data Set (BCWD) and Heart Disease Data Set (HDD). The. Simulation results showed that the proposed DPMMSD-HECC model has outperformed all of the other techniques in a number of ways.
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