A Novel Approach to Secure IoMT: Hybrid Blockchain and ML-Based IDS

The Internet of Medical Things (IoMT) revolutionizes healthcare by integrating medical devices with health systems, creating unprecedented opportunities for patient monitoring and treatment. However, this integration also introduces significant cybersecurity risks, including data breaches, unauthorized access, and cyberattacks on medical devices. This paper proposes a novel hybrid security framework that combines blockchain technology with machine learning-based Intrusion Detection Systems (IDS) to address these risks and secure IoMT networks. The blockchain component of the framework ensures data integrity and secure transactions through decentralized, immutable ledgers, which prevent tampering and unauthorized data modifications. Each transaction is recorded in a secure, transparent manner, enhancing trust among stakeholders. The IDS component employs advanced machine learning algorithms to perform real-time threat detection and response, analyzing network traffic to promptly identify and mitigate potential cyber threats. Our evaluation shows the proposed hybrid approach can detect malicious attacks on IoMT network with a high accuracy.