BLOCKCHAIN-INTEGRATED SECURE DATA MANAGEMENT ARCHITECTURE FOR FOG-EDGE NETWORKS IN HEALTHCARE MONITORING SYSTEMS

Abstract

The rapid proliferation of Internet of Medical Things (IoMT) devices in remote and continuous healthcare monitoring generates massive volumes of sensitive physiological data, exposing traditional centralized cloud architectures to unacceptable latency, single points of failure, privacy breaches, and scalability limitations. This review examines the integration of blockchain technology with hierarchical fog-edge-cloud (EFC) computing as a transformative paradigm for secure, decentralized data management in healthcare systems. Blockchain provides immutable audit trails, tamper-resistant storage, transparent access control, and patient-centric data ownership through smart contracts, while fog and edge layers enable low-latency preprocessing, real-time anomaly detection, and localized decision-making for time-critical signals (ECG, EEG, vital signs). Key architectural components include lightweight consensus mechanisms (PBFT variants, PoS, G-PBFT), cryptographic primitives (ECC, SHA-256, zero-knowledge proofs), role-based access control (RBAC) enhanced by smart contracts, and hybrid off-chain/on-chain storage models to balance performance and security. The framework addresses regulatory compliance (HIPAA, GDPR), interoperability challenges, and energy constraints in resource-limited edge nodes. Case studies demonstrate reduced latency (up to 90% compared to pure cloud), enhanced privacy, and resilience against tampering and single-point failures. Future directions emphasize scalable consortium blockchains, AI-driven anomaly detection at the edge, and standardization to accelerate clinical adoption of blockchain-integrated fog-edge healthcare monitoring.