Secure and Resilient: An Integrated Methodology for Enhancing Electronic Health Record (EHR) Data Security and Privacy in Healthcare

Secure Electronic Healthcare Records (EHR) data is critical for protecting patient privacy and safeguarding the integrity of medical information. The requirement for strong security measures in healthcare data stems from the sensitive nature of the information involved, which includes personal identifiers and medical histories. This study explores existing techniques to securing healthcare data, outlining their shortcomings and proposing a unique methodology to address these difficulties. To manage healthcare data, the study takes a multimodal approach. It starts from the Synthea TM dataset and uses BERT -CNN for standardization. Game theory-based hyperparameter adjustment is used to maximize its performance. Full homomorphic encryption (TFHE) is then included for improved data security. Using RESTful API on the Ethereum blockchain, authentication is strengthened. An additional degree of protection is added with homomorphic encryption using decentralized identifiers. With the use of blockchain and homomorphic encryption, cloud infrastructure provides scalable and secure health data storage. Integrating the Ethereum blockchain strengthens storage that is both secure and decentralized. Using advanced technologies, this complete technique tackles the difficulties of security, standardization, and storage in the administration of healthcare data. Scalability, accessibility, and strict security requirements are met by this integrated method, which ensures standardized, safe, and privacy-preserving healthcare data management. With an average increase of almost 23%, the suggested Game Theory (GT) with BERT -CNN (99%) approach shows a significant improvement in accuracy over the current methods. The usefulness of the proposed model in improving the accuracy of the classification task over BERT and Random Forest approaches is highlighted by this noteworthy development, as demonstrated by the stated accuracy percentages. Together, these initiatives aim to bring about in a future in which patient outcomes are significantly improved by the secure handling, storage, analysis, and responsible use of medical data across the healthcare ecosystem.