The AutoTRUST project aims to develop and demonstrate a novel AI-leveraged self-adaptive framework of advanced vehicle technologies and solutions which optimize usability, perception, and experience on-board, and when boarding/off-boarding, in terms of security, privacy, well-being, health and assistance. AutoTRUST provides enhanced inclusiveness and trust in the interaction between users and new automated modes of road transport and mobility services in the transition from human-driven to automated vehicles. Safety and security of vehicle occupants in all circumstances even when the vehicle is driverless by helping to prevent dangerous and inconvenient situations will be of paramount importance. Intense cooperation between users, vehicle manufacturers, suppliers, researchers, and other stakeholders to co-design vehicles with solutions that optimize the on-board experience will be adopted. Moreover, an in-depth knowledge of the benefits of new vehicle technologies and solutions in terms of on-board experience, accessibility, inclusiveness, and trust will be acquired to enable wider user acceptability and contribute to the creation of future standards.

The contemporary AI landscape demands a holistic framework ensuring security across the supply chain and entire AI lifecycle. Despite existing adversarial attack techniques, a comprehensive end-to-end flow for identifying threats and vulnerabilities with associated risks is lacking. The EU, through initiatives like the AI Act, emphasizes safety and trustworthiness in AI applications but lacks a system managing weaknesses in a networked AI-supply chain. The CoEvolution project integrates its architecture components to create an end-to-end Security, Trust, and Robustness (STR) assessment solution, generating context-aware AI models characterized by their AI Model Bill of Materials (AIMBOM). The goal is a universal hub providing a coherent STR risk assessment and security assurance flow, aligning with MLDevOps and EU AI regulatory frameworks. The paradigm includes novel AI model descriptions, AIMBOM management, security monitoring, and context awareness. CoEvolution introduces a new STR paradigm based on Bills-of-Materials, offering a unified approach to describing AI models in supply chains, ensuring STR compliance with EU directives on trust, fairness, data governance, and GDPR guidelines. Open source trusted datasets and CoEvolution-developed AI models enhance the hub's capabilities, aiming for a robust, adaptable risk analysis and security assessment framework aligned with evolving AI cybersecurity threats.