Reliable Routing for V2X Networks: A Joint Perspective of Trust-Prediction and Attack-Resistance

In intelligent transportation systems, data routing in vehicle-to-everything (V2X) networks is key to ensuring efficient information transfer among vehicles, pedestrians and infrastructure. The quality of data routing directly affects communication efficiency and system performance. However, data routing in V2X networks often faces potential security threats, which may lead to communication interruption, data delay or information loss. Unreliable routing fails to meet the communication quality of service (QoS) requirements for V2X networks. Therefore, this paper proposes a joint scheme that combines trust-prediction and attack-resistance to ensure reliable routing in V2X networks. First, this scheme employs a fuzzy control-based trust evaluation method to provide direct trust indicators. Second, a trust prediction method based on deep belief networks is utilized to evaluate vehicle status. A classification scheme based on trust levels is used to filter candidate sets for network repair to help the network resist malicious behaviour. Last, a novel routing decision function is introduced to plan reliable routes. Routes planned on the basis of this function not only meet the basic requirements of reliable routing, but are also suitable for routing requirements in different scenarios, such as minimizing transmission latency. The Experimental results show that, compared with the three baseline schemes, this scheme improves the accuracy and false alarm rate on the UNSW-NB15 dataset by 2.94% and 6.31%, respectively, and this scheme also performs better in terms of the data reception rate and transmission delay rate in actual application scenarios.