Secure gene profile data processing using lightweight cryptography and blockchain

Human microarray gene profile analysis has become popular for early cancer detection. Due to security risks, Healthcare 4.0 standards make processing patient gene data difficult. Healthcare 4.0 guidelines must secure gene profile data storage and exchange. Recently several blockchain-based methods have been proposed for secure data processing for Cloud-based Healthcare 4.0 architecture. However, existing solutions not providing all the essential features like scalability, strong security measures, computational efficiency, and multiple security parameters. To overcome these problems, we propose a novel approach for the secure processing of the microarray gene expression data using computationally efficient, scalable, and highly secured Healthcare 4.0 standards. We propose a new Healthcare 4.0 architecture based on lightweight cryptography and blockchain technologies. Blockchain technology's recent advancements in cloud data storage and sharing indicate potential security features. Smart healthcare applications need a centralized approach for safe data storage and exchange. Edge layer (patients/gene users), fog, cloud storage, and blockchain make up Healthcare 4.0. Fog nodes store and search edge-layer gene data in blockchain-enabled cloud storage using lightweight cryptography. Elliptic Curve Cryptography (ECC) protects data processing and privacy using Elliptic Curve Diffie-Hellman (ECDH) and Elliptic Curve Digital Signature Algorithm (ECDSA). Meta-data from cloud-saved data is stored in blockchain to prevent tampering, forging, and quantum. We designed different threat-based case studies to demonstrate the model's efficiency and scalability. Computing efficiency and security are better with the proposed strategy. The outcome case studies showed that the suggested approach protected against various opponent models. The proposed method reduces encryption and decryption times by 325 and 20 ms, respectively.