Trust Evaluation Method

Trust evaluation methods aim to quantify and verify trust relationships between entities, crucial for secure and efficient interactions in diverse systems, from e-commerce to autonomous AI. Current research focuses on integrating different trust mechanisms (e.g., policy-based and reputation-based), employing formal verification techniques like Event-B for rigorous analysis, and leveraging machine learning, particularly graph neural networks (GNNs), to model and predict trust dynamically and robustly. These advancements are significant for improving the security and reliability of complex systems involving human-AI collaboration, data sharing, and automated decision-making.