Evidence Based Trust Scoring for Multimodal VANET Applications

Trust and security management in modern Intelligent Transport System (ITS) is a demanding task. In a recent publication a Large Scale Multimodal Data Processing Middleware for Intelligent Transport Systems (LDPM) was introduced. This LDPM depicts an ITS that utilises cryptographic and trust based technologies to provide secure Vehicular Ad-Hoc Network (VANET) communication. However, some critical aspects regarding evidence evaluation and trust scoring were subjected to future work. These topics are now addressed in this paper. Thus, a novel scheme to describe traffic related evidence in a multimodal environment, a modified version of a Bayesian Inference (BI) function, and a comprehensive data centric trust management method is presented. These findings integrate into the LDPM, but are also applicable in a stand alone solution. These goals were accomplished, as demonstrated in the final performance evaluation.