With the swift advancement of the Internet of Things (IoT), Vehicular Ad Hoc Networks (VANETs) have become a crucial component in enabling smart transportation systems by supporting real-time communication between vehicles and roadside units (RSUs). In these networks, vehicles function as mobile nodes that generate and transmit data across the system. A major challenge in VANETs is ensuring the integrity and trustworthiness of shared messages, as any malicious or inaccurate information could severely impact safety and system performance. This research introduces a trust management framework that integrates VANET with blockchain technology and fuzzy logic to improve the reliability of vehicle-to-vehicle communication. When an event is detected, a vehicle instantly broadcasts a corresponding message. RSUs then evaluate the sender’s trust level and verify the message before validation. To minimize communication overhead and avoid duplication, repeated messages are filtered prior to distribution. Unlike conventional trust models that depend on computationally heavy consensus mechanisms such as Proof of Work (PoW), the proposed system adopts a Chord-based distributed architecture. This approach significantly lowers processing times and boosts scalability. The framework utilizes a multi-phase trust evaluation process involving message scoring, dynamic trust calculation, and formation of evaluator groups by RSUs. Simulations reveal notable gains in message credibility: a 6% increase compared to the Score-Based Trust Management System (SBTMS) and an 11% improvement over PoW-based approaches. These results underline the effectiveness of the proposed model in achieving a balance between security, scalability, and low latency in VANET environments. By merging VANET architecture with decentralized trust mechanisms and soft computing techniques, this study presents an innovative and pragmatic solution to one of the key challenges in vehicular communications—facilitating secure, efficient, and trustworthy message exchange in highly dynamic, distributed networks.
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