Blockchain-Enabled Cybersecurity Framework for Safeguarding Patient Data in Medical Informatics
Prajakta Uday Waghe, A. Suresh Kumar, Arun B Prasad, Vuda Sreenivasa Rao, E. Thenmozhi, Sanjiv Rao Godla, Yousef A. Baker El–Ebiary · International Journal of Advanced Computer Science and Applications · 2024
Securing patient information is crucial in the quickly changing field of healthcare informatics to guarantee privacy, reliability, and adherence to legal requirements. This article presents a complete cybersecurity architecture enabled by blockchain and customized for the medical informatics area. The framework initiatives to provide adequate safeguards for sensitive patient data by utilizing AES-Diffie-Hellman key exchange for secure communication, blockchain technology with Proof-of-Work (PoW), and Role-Based Access Control (RBAC) for fine access management. A strong cybersecurity architecture is crucial for maintaining the security, credibility, and availability of private patient information in the current healthcare information management environment. By using decentralized storage, access control methods, and cutting-edge encryption strategies, the suggested framework overcomes these difficulties. The framework ensures safe data transport and storage by showcasing effective AES encryption as well as decryption procedures through performance evaluation. PoW consensus combined with blockchain technology provides the framework with auditable and immutable data storage, reducing the possibility of data manipulation and unwanted access. Additionally, granular access control is made possible by the integration of RBAC, guaranteeing that only those with the proper authorization may access patient data. Python is used to implement the suggested framework. The suggested method considerably outperformed NTRU, RSA, and DES with encryption and decryption times of 12.1 and 12.2 seconds, respectively. The proposed Blockchain-Enabled Cybersecurity Framework demonstrates exceptional efficacy, evidenced by its ability to achieve a 97.9% reduction in unauthorized access incidents, thus offering robust protection for patient data in medical informatics.