CONNECT not only achieved its primary goal of enabling the secure and trustworthy exchange of CCAM information, through CCAM-wide trust quantification based on subjective logic and runtime evidence, but also established a comprehensive trust plane across vehicles and infrastructure, including both the central cloud and the Multi-Access Edge Computing (MEC) environment, thereby extending operational boundaries. The framework advances the vision of disaggregating services across the compute continuum, leveraging emerging networking technologies such as (B)5G and MEC to optimize latency and resource availability closer to the edge. It integrates infrastructure entities beyond traditional cloud-based services , such as traffic control centers and intersection movement assistance services, as well as centralized security solutions like PKIs. By incorporating MEC, CONNECT enables the secure offloading of tasks from vehicles to MEC nodes, providing abundant computational resources for efficient task execution and resource management.
To operationalize CCAM-wide trust quantification, CONNECT’s framework functions in two complementary phases. The Design phase establishes trust models, defines the types of evidence to monitor, and deploys trust-related components across the ecosystem. The Runtime phase executes attestation and continuously monitors system configuration integrity. Importantly, CONNECT not only provides the necessary hardware-rooted evidence for trust assessment but also extends existing solutions through the integration of Misbehavior Detection, ensuring convergence with the overall trust assessment process. Evidence is harmonized and abstracted before transmission to protect privacy, allowing comparison against the Required Trust Level (RTL) and enabling comprehensive trust assessment across all CCAM resources and actors.
