This model demonstrates enhanced data security and user authentication in WBAN, suggesting effective privacy preservation methods.
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.
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Chandra et al. (2025) studied this question.
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