Trust Assessment in Vehicular Social Network Based on Three-Valued Subjective Logic

Abstract

Trustworthiness in a vehicular network plays a vital role in facilitating data sharing among vehicles to achieve better driving safety and convenience. Without trustworthiness assessment, a vehicle may not be able to trust other vehicles and, therefore, simply drop the data shared from others to avoid potential driving dangers. This problem was traditionally approached by protecting data security; however, the study of the trustworthiness of data generators (vehicles) is unfortunately omitted. We envision the existences of a vehicular social network on road, wherein vehicles exchanging data between each other are considered socially connected. Leveraging the trust propagation and fusion within a vehicular social network, the trustworthiness of individual vehicles can be accurately assessed. We adopt the three-valued subjective logic model to study trust between vehicles, and propose a holistic solution to trust assessment in vehicular social networks. The proposed solution enables objective and subjective trust assessment of vehicles, in a distributed manner. Simulation results indicate that the proposed solution offers a more accurate trust assessment and a quicker assessing time.