An Enhanced Hybrid Encryption-BlockChain Security Framework for IoMT Data Preservation
TL;DR
The findings demonstrate that the framework addresses IoMT security and privacy limitations by combining hybrid encryption with decentralized blockchain technology, providing a scalable, efficient, tamper-resistant, and trustworthy solution for next generation healthcare systems.
Abstract
The Internet of Medical Things (IoMT) has transformed healthcare by enabling continuous patient monitoring and exchange of physiological data. However, conventional IoMT systems rely on centralized cloud infrastructures vulnerable to unauthorized access, privacy breaches, data tampering, and single points of failure. This study presents an enhanced hybrid encryption-blockchain security framework for IoMT data preservation to improve data security, integrity, and availability. The framework integrates Advanced Encryption Standard (AES-256-GCM) for authenticated data encryption with Elliptic Curve Cryptography (ECC-SECP256R1) for secure key generation and exchange. A three-layer storage architecture combines a local SQLite database for low-latency access, a PHP/MySQL authenticated cloud backup server for redundancy and disaster recovery, and a blockchain ledger for immutable integrity verification and transaction auditing. A real-time physiological dataset was generated using a webcam-based Chrominance Photoplethysmography (rPPG) model implemented in JavaScript to estimate heart rate from facial video streams through facial landmark detection. The system was developed using the Agile Software Development Methodology, with Python 3.9 as the server-side language. Performance evaluation considered heart rate estimation accuracy, encryption and decryption latency, blockchain transaction validation time, backup reliability, storage overhead, and tamper detection capability. Results demonstrated high heart rate estimation accuracy, encryption times below 5 ms per medical record, efficient key exchange, reliable cloud backup, low-latency blockchain verification, and strong detection of simulated data tampering. The findings demonstrate that the framework addresses IoMT security and privacy limitations by combining hybrid encryption with decentralized blockchain technology, providing a scalable, efficient, tamper-resistant, and trustworthy solution for next generation healthcare systems.