Monitoring Intelligent Connected Vehicles: Embedding Trust Levels in Status Within Zero-Trust Network Architecture

This paper investigates the problem of distributed state monitoring for intelligent connected vehicle (ICV) fleets based on embedded trust levels within a zero-trust network architecture (ZTNA) while considering the impact of unknown input disturbances. The ZTNA significantly enhances the overall security performance of the vehicle fleet. To implement the “never trust, always verify” principle, we first analyze the effects of zero-trust architecture on the communication relationships among intelligent connected vehicles (ICVs). Drawing inspiration from human trust dynamics, rules for establishing and reducing trust levels between vehicles are formulated. A variable-directed graph is employed to represent the communication topology of the entire vehicle fleet. Next, a distributed unknown input monitor structure is proposed using known information and verified global state monitoring results from neighboring vehicles with embedded trust levels. By utilizing selectable matrices to process local and global control inputs, any individual vehicle can monitor the state of the entire fleet. Finally, a simulation analysis of a fleet of six vehicle nodes demonstrates the correctness and effectiveness of the proposed method.