10156971Sparc: Secure Platform for Authenticated and Reliable data exchange in Connected vehiclesClosedCollaborative R&DInnovate UKThe Trust-Based Management Platform for Secure and Reliable Data Exchange in Connected Vehicle Networks is designed to address the growing need for trust and security in modern transportation systems. As vehicles become more connected, they rely heavily on real-time data exchanges for navigation, collision avoidance, and traffic management. However, inaccurate, malicious, or compromised data can lead to severe consequences, including accidents, congestion, and loss of trust in the entire ecosystem. Our platform introduces a dynamic trust scoring mechanism, similar to credit scores used in financial systems, to evaluate the reliability of data sources within vehicle networks. By integrating machine learning, federated learning, and blockchain, the platform ensures that only trusted and verifiable data is used for critical decision-making. At the core of this solution is AI-driven anomaly detection, which continuously monitors vehicle communications, identifies inconsistencies, and differentiates between malfunctioning and potentially malicious data sources. By analysing packet integrity, transmission delays, and data consistency, the system assigns dynamic trust scores to vehicles and roadside units (RSUs). These scores help determine whether shared data can be relied upon for making crucial decisions. Additionally, blockchain-based trust ledgers ensure a decentralized, tamper-proof, and transparent system where trust scores are securely maintained and updated. This approach significantly improves the reliability of connected vehicle networks by preventing the propagation of false or compromised data. To further enhance security and efficiency, the platform incorporates federated learning, allowing vehicles and RSUs to collaboratively refine trust models while preserving data privacy. Unlike traditional centralized learning methods, federated learning ensures that raw data remains within its source, reducing the risk of unauthorized access or exploitation. This decentralized approach enables trust evaluation to evolve over time, adapting to new threats and dynamic traffic conditions. The platform's real-time trust evaluation and rapid decision-making capabilities are crucial for improving road safety and traffic efficiency. By designating roadside units as temporary trust anchors, the system enables fast and reliable validation of vehicle data across multi-hop networks. This ensures that only trustworthy data influences decisions related to autonomous driving, traffic optimization, and emergency response. Beyond connected vehicles, this trust-based approach has broader applications in smart cities, industrial IoT networks, and autonomous logistics systems, where data integrity is equally vital. By integrating trust-aware decision-making into connected vehicle ecosystems, this platform enhances transportation security, ensures data reliability, and fosters a safer, more efficient mobility future.