Privacy-Preserving Medical Cloud Architecture Using Hybrid Key Encryption and Blockchain-Based Verification

The proliferation of healthcare data and the increasing reliance on cloud infrastructures have intensified concerns about security, data privacy, and accessibility. Addressing the critical challenge of safeguarding sensitive patient information, this study proposes a new hybrid encryption architecture that integrates Principal Component Analysis (PCA)-based compression, a fall webworm optimization (FWW)-driven S-box encryption mechanism (FWW-S), and blockchain enabled secure data transmission. The model capitalizes on the dimensionality reduction capabilities of PCA to efficiently compress medical data while preserving critical diagnostic features. The bio-inspired FWW algorithm is employed to dynamically generate high-entropy cryptographic keys through an optimized S-box structure, enhancing encryption robustness and key diversity. Encrypted and compressed data is subsequently transmitted via a blockchain protocol to ensure tamper-proof, traceable, and decentralized data sharing. The suggested method overcomes the drawbacks of traditional hybrid encryption approaches, especially with regard to computational effectiveness and key generation flexibility. Simulation results confirm the effectiveness of the FWW-S framework in maintaining data confidentiality, integrity, and authentication within distributed healthcare systems. The scheme demonstrates significant improvements in encryption/decryption time, storage efficiency, energy consumption, and resistance to unauthorized access. By successfully balancing data sharing with privacy protection, this work offers a scalable and secure solution for next-generation medical cloud computing environments.