Blockchain-Based HSFO Framework for Privacy Preservation of Health Care Data Using Hybrid Algorithms

Digital transformation of healthcare has led to widespread adoption of Electronic Health Records (EHRs), significantly enhancing the accessibility and efficiency of clinical workflows, administrative processes and biomedical research. Given the highly sensitive nature of patient data, ensuring its confidentiality, integrity and controlled access is paramount. However, conventional EHR systems predominantly rely on centralized storage architectures, which are vulnerable to unauthorized access, data breaches and insider threats, posing severe privacy and security concerns. To address these challenges, blockchain technology offers a promising decentralized infrastructure characterized by immutability, transparency and distributed trust. By integrating smart contracts and secure transaction logging, blockchain strengthens data provenance and enforces auditable access control in healthcare systems. Complementing this, encryption techniques are essential for maintaining confidentiality; however, traditional key generation and management approaches often lack adaptability and entropy, limiting their robustness in dynamic threat landscapes. This paper proposes a novel hybrid optimization framework that combines the Sunflower Optimization Algorithm (SFO) and Firefly Algorithm (FA) within a blockchain-enabled architecture. SFO is employed to generate high-entropy cryptographic keys, ensuring resistance to brute-force attacks, while FA models user behavior to assign dynamic trust scores, facilitating behavior-aware access control policies. The novelty lies in the integration of adaptive key management with real-time behavioral analytics, enforced via smart contracts on a blockchain network, thereby enabling proactive and context-aware privacy protection. Experimental results validate the effectiveness of the proposed system. The hybrid algorithm achieves superior entropy in key generation compared to conventional methods, over 93% accuracy in access decision-making and responsive smart contract-based re-keying triggered by trust deviations. Furthermore, the blockchain layer maintains scalable throughput and acceptable latency under varying transaction loads. Collectively, the approach offers a robust, decentralized and intelligent framework for safeguarding EHR privacy in modern healthcare ecosystems.