An Efficient and Secure WBAN Based on Optimal Privacy Preservation Scheme With Deep Learning and Blockchain Technology

IF 2.5 4区 计算机科学 Q3 TELECOMMUNICATIONS
Balasubramanian Chandra, Subramanian Kanaga Suba Raja, Suresh Sudha
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Abstract

Securing the trustworthiness, privacy, and legitimacy of shared medical data in Wireless Body Area Network (WBAN) is a primary concern. Hence, a blockchain technology-based secure medical data storage scheme is developed in this paper. This developed model includes four primary phases. Before initializing, the WBAN data are collected. In the first phase, the user authentication is verified. For this purpose, the user's iris images are aggregated. These iris images are subjected to the Residual Attention Network (RAN). From the RAN, the user is authorized, and then security keys are given to the authorized user. Only after verifying the authentication of the user, the healthcare data is allowed to be stored in the blockchain. In the second phase, data sanitization takes place. The obtained WBAN medical data are sanitized using a data sanitization process with the optimal keys obtained from the Fusion of Golden Eagle and Eurasian Oystercatcher Optimization Algorithm (FGE-EOOA). Here, the data are encrypted by employing the Rivest-Shamir-Adleman (RSA) approach, and then encrypted medical data are stored in the blockchain. This ensures multi-step data security, which allows secure storage of WBAN healthcare data in the blockchain. While retrieving the stored data, the user authentication is verified on the user side, as well as in the same RAN model. This is the third phase of the developed model. When the user is proven to be an authorized one, the stored data in the blockchain corresponding to that particular user is retrieved. Using the data restoration process, which is the fourth phase of the developed model, the actual medical data is retrieved. If the user is unauthorized, then no access is provided to them. This ensures a multi-level of security for storing and retrieving data from the blockchain. The security offered by this model is evaluated and validated by contrasting and comparing it with other conventional data transfer methods.

Abstract Image

基于深度学习和区块链技术的高效安全WBAN最优隐私保护方案
确保无线体域网络(WBAN)中共享医疗数据的可信度、隐私性和合法性是一个主要问题。为此,本文提出了一种基于区块链技术的医疗数据安全存储方案。这个发展的模型包括四个主要阶段。在初始化之前,收集WBAN数据。在第一阶段,验证用户身份验证。为此,用户的虹膜图像被聚合。这些虹膜图像经过剩余注意网络(RAN)处理。从RAN中对用户进行授权,然后向授权用户提供安全密钥。只有在验证用户身份验证后,才允许将医疗保健数据存储在区块链中。在第二阶段,进行数据清理。利用金鹰与欧亚捕牡蛎优化算法(FGE-EOOA)融合得到的最优密钥对获取的WBAN医疗数据进行数据消毒。在这里,通过使用RSA (Rivest-Shamir-Adleman)方法对数据进行加密,然后将加密的医疗数据存储在区块链中。这可确保多步骤数据安全性,从而允许在区块链中安全地存储WBAN医疗保健数据。在检索存储的数据时,在用户端以及在相同的RAN模型中验证用户身份验证。这是已开发模型的第三阶段。当证明该用户是经过授权的用户时,将检索与该特定用户对应的区块链中存储的数据。使用数据恢复过程(这是所开发模型的第四个阶段)检索实际的医疗数据。如果用户未经授权,则不向他们提供访问权限。这确保了从区块链存储和检索数据的多级安全性。通过与其他传统数据传输方法的对比,对该模型的安全性进行了评价和验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.90
自引率
13.90%
发文量
249
期刊介绍: ransactions on Emerging Telecommunications Technologies (ETT), formerly known as European Transactions on Telecommunications (ETT), has the following aims: - to attract cutting-edge publications from leading researchers and research groups around the world - to become a highly cited source of timely research findings in emerging fields of telecommunications - to limit revision and publication cycles to a few months and thus significantly increase attractiveness to publish - to become the leading journal for publishing the latest developments in telecommunications
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