Performance and security analysis of fully homomorphic encryption in cloud-based healthcare blockchain.

Abstract

Objective: This study evaluates the feasibility and performance of a cloud-based healthcare blockchain framework that integrates Fully Homomorphic Encryption (FHE), Extended Secure Searchable Encryption (ESSE), and Attribute-Based Signature (ABS) for managing encrypted Personal Health Records (PHRs). Methods: A synthetic dataset of 1,000 anonymized health records, modeled after the publicly available Cell-Phone Brain Tumour dataset (Kaggle), was generated in MATLAB. The dataset emulated attributes typically collected by IoT-enabled or mobile health devices (e.g., usage duration, radiation exposure), although no physical IoT integration was implemented. The cryptographic modules-FHE, ESSE, and ABS-were implemented and simulated in a MATLAB-based cloud environment. System evaluation focused on encryption latency, query throughput, access control accuracy, and overall operational efficiency. Results: The FHE module achieved an average encryption time of 2.5 s and a computation time of 4.8 s per 1 KB record. ESSE sustained 20 encrypted queries per second with an 85% success rate. ABS enforced decentralized access with 97% accuracy and a false positive rate of 0.002%. When integrated, the system reached 94% operational efficiency across simulated healthcare workloads. Conclusion: The proposed FHE-ESSE-ABS framework advances existing healthcare blockchain solutions by enabling encrypted computation, privacy-preserving search, and fine-grained access control. These findings confirm its feasibility for secure cloud-based healthcare data management and establish a foundation for future real-world deployment in health informatics.