Trust Level Evaluation Engine for Dynamic Trust Assessment with Reference to Subjective Logic

We propose an architectural design for a Trust Level Evaluation Engine. The engine is meant to work in a complex and dynamic environment of potentially untrustworthy sources of information where the situational knowledge is partial and subjective from the viewpoint of the information source, thus potentially inconsistent and contradictory. Consistently with a Zero-Trust approach, no initial trust between nodes should be assumed, since a decision-making module shall nevertheless figure out its level of confidence about the truth of a proposition over the reality. Our design is theory-agnostic and can be instantiated on different mathematical subjective model theories, but we demonstrate its feasibility by mapping it on the Subjective Logic. We also discuss critical design choices and algorithmic details that are only partially addressed in the abstract description of the theory, and we demonstrate how the engine effectively works on large and complex subjective trust networks. Additionally, we offer a proof-of-concept implementation to showcase the proposed architecture’s ability to handle intricate and complex networks.