A Decentralized Secure Blockchain Model and Lightweight Cryptosystem for Enhancing the EHR Data Security
Jyothy Sondekola Tippeswamy, Mrinal Sarvagya · Transactions on Emerging Telecommunications Technologies · 2025
ABSTRACT Purpose An electronic health record (EHR) is a sensitive collection of data about the health of many people in a smart healthcare system. Because of the importance of persons in smart healthcare systems, an effective security architecture is critical for maintaining privacy in Electronic Health Records (EHRs) databases. EHRs are often stored on centralized servers, which increases the risk of security breaches and necessitates trust in a single authority that cannot adequately protect data from internal threats. Objectives This research focuses on protecting patient privacy and data security during sensitive data transmission between healthcare providers for diagnosis. This paper describes a methodology for developing a revolutionary decentralized, secure blockchain model and lightweight cryptosystem to improve EHR data security. Methods The EHR data are initially collected from the dataset, and the user transaction information is initialized for communication between multiple nodes. Here, the medical data are double encrypted using the Integrated ElGamal Hyper Elliptic cryptosystem (IntEH), whereas the public and private keys can be generated using an elliptic scheme to enhance the security of health data. For added protection, the encrypted data is held on the off‐chain Inter Planetary File System (OIPFS) blockchain. Results For the proposed model, several performance measures are examined, including key generation time, execution time, encryption time, and throughput. Compared to other existing models, the proposed model can achieve a lower key generation time of 152 s for the healthcare dataset. Conclusion The analytical results show the performance of the proposed design, which reflects the proposed strategy, which gives a lower delay rate in milliseconds and a higher data loss ratio at various patient block counts.