Blockchain-Powered Patient-Centric Access Control with MIDC AES-256 Encryption for Enhanced Healthcare Data Security

Krishna Prasad Narasimha Rao and Selvan Chinnaiyan

Acta Informatica Pragensia, 2024, vol. 2024, issue 3, 374-394

Abstract: Patient-centric access control in healthcare data management is paramount for ensuring privacy, confidentiality and security. In this paper, we propose a novel blockchain-powered patient-centric access control system integrated with MIDC AES-256 encryption to enhance healthcare data security. The proposed system prioritizes patient autonomy by granting patients control over access to their detailed health information, while hospitals are authorized to share relevant medical history. Using blockchain technology ensures decentralization, transparency and immutability of data, while smart contracts and consensus mechanisms enforce accountability and integrity. Additionally, the system employs MIDC AES-256 encryption, which combines multi-input data concatenation (MIDC) with AES-256 encryption, optimizing data integrity and security. The study involves a comparative analysis with existing methods including ABE, RSA and hybrid algorithm AES. The results demonstrate the superiority of our proposed system in terms of encryption speed, decryption time and memory usage. The proposed system achieves an encryption time of 3.8 seconds and a decryption time of 3.2 seconds, significantly outperforming ABE, RSA and hybrid algorithm AES. Moreover, the system exhibits lower memory usage (0.146 MB), highlighting its efficiency and scalability. The proposed system is implemented in Python, providing a versatile and accessible solution for healthcare data security enhancement. Through blockchain-powered patient-centric access control and MIDC AES-256 encryption, our system offers a robust framework for securing sensitive healthcare information while prioritizing patient privacy and control.

Keywords: Patient-centric access control; Healthcare data management; MIDC AES-256 encryption; Blockchain technology; Multi-input data concatenation (search for similar items in EconPapers)
Date: 2024
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DOI: 10.18267/j.aip.242

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