Trust Aware and Explainable Access Control for Internet of Medical Things: A Lightweight Hybrid Blockchain Approach

The Internet of Medical Things (IoMT) permits continuous patient monitoring, remote diagnosis, and intelligent clinical decision support using networked medical devices. However, IoMT environments are very challenging, given their stringent latency requirements, device diversity and dynamic clinical workflows which hinder traditional static access control (AC) approaches performing effectively. Traditional access control systems such as Role Based Access Control (RBAC) and fixed Attribute Based Access Control (ABAC) fail to adapt to real-time contextual changes, evolving user behavior, and trust dynamics in medical IoT systems. In addition, AI driven Access Control (AC) solutions often operate as black box models, limiting transparency and regulatory compliance. This paper proposes a trust aware and explainable AC framework specifically designed for IoMT systems, integrating a tree based ensemble learning model for trust evaluation, explainable artificial intelligence (XAI), and a lightweight hybrid blockchain architecture suitable for real-time IoMT deployments. The framework dynamically evaluates access requests using contextual and behavioral attributes and generates human interpretable explanations for each access decision using SHAP-based XAI, enabling transparency and compliance with healthcare regulations. To meet IoMT latency and scalability requirements, computationally intensive machine learning (ML) and explainability tasks are executed off-chain, while access decisions and audit logs are immutably recorded using a hybrid blockchain composed of Hyperledger Fabric and Hyperledger Besu. A prototype implementation in a realistic IoMT environment demonstrates that the proposed framework achieves an access decision accuracy of 93.4%, with an average end to end latency of 1.8 seconds, which is suitable for real-time medical workflows. The off-chain AI integration reduces blockchain execution costs by 81% compared to fully on-chain solutions, while preserving security, auditability, and system reliability. These results indicate that trust aware and explainable access control can significantly enhance the security, transparency, and operational robustness of next generation IoMT systems.