FedTrust: Modelling Adaptive Trust-Risk for IoT-Enabled Federated Decentralized Systems

Federated decentralized IoT systems are reshaping how data is exchanged and processed across domains such as smart cities and healthcare, yet ensuring trust in such dynamic, distributed environments remains a significant challenge. This paper introduces FedTrust, a layered framework that integrates decentralized communication, federated data services, and a self-adaptive trust-risk model to assess the trustworthiness of IoT devices in real time. By extending an established analytical trust model, we refine existing constructs and introduce new dimensions such as context awareness and behavioral monitoring to account for the operational variability of edge devices. Our proposed model computes risk and trust scores using weighted metrics, driving automated decisions and mitigation actions via a closed feedback loop. FedTrust provides a scalable and resilient approach for securing federated IoT ecosystems through continuous, data-driven trust calibration.