Direct and Indirect Trust Evaluation for Healthcare Internet of Things

The influence of Internet of things on modern infrastructure is high which can be integrated with other fields in our work healthcare community to make an advancement in the healthcare IoT field to monitor and easy access. However, the heterogeneous and autonomous nature of these devices introduces challenges related to trust, honesty, and reliability. Unreliable or misleading data-whether due to technical malfunctions or adversarial manipulation-can severely impact decision-making in health-critical scenarios. This paper presents a novel trust evaluation model specifically designed for H-IoT environments inspired by the Social Internet of Things (SIoT) framework. The proposed model introduces a computational trust scoring mechanism that integrates honesty, device reliability, and health risk awareness into a unified decision-making protocol. By leveraging both direct behaviour observations and regression-based accuracy assessments, the model dynamically calculates a trust score for each device, enabling trustworthy interactions and improving overall system resilience. Comparative analysis with traditional trust models demonstrates the superior performance and adaptability of our model in real-world healthcare scenarios.