M-ECDH: A NOVEL KEY GENERATION SCHEME FOR SECURE CLOUD-BASED HEALTHCARE SYSTEMS

Abstract

Cloud computing has developed into a core element of the healthcare sector, enabling efficient maintenance and preservation of electronic medical records (EMRs), diagnostic images, and patient data. While offering significant flexibility and cost savings, cloud utilization also poses significant security and privacy concerns. This addresses advanced cloud security techniques for protecting private medical information in distributed health environments. We first leverage Attribute-Based Encryption (ABE) for fine-grained role-based access control and privacy-preserving encryption to ensure that only the intended users with specific roles and attributes can access sensitive data. Besides enabling additional cryptographic strength, we propose a Modified Elliptic Curve Diffie Hellman (M-ECDH) key generation scheme that incorporates behavioral signals for secure and dynamic key exchange. Finally, the encrypted information is stored in a decentralized IPFS-based blockchain platform that offers immutable, tamper-proof, and distributed data storage. The proposed framework offers a scalable, effective, and secure architecture suitable for modern cloud-based healthcare systems that address current and future threats as well as meeting data protection requirements. Experimental results demonstrate improved performance in key generation time (64 ms), encryption/decryption speed, reduced storage redundancy (9%), and improved security over existing approaches.