Highly dynamic topology and unreliable vehicular behaviors remain major challenges for blockchain-enabled trust management in Vehicular Ad Hoc Networks (VANETs). Conventional blockchain schemes often suffer from excessive consensus latency, communication overhead, and limited scalability in dense vehicular environments. To address these limitations, this paper proposes a lightweight DAG-blockchain framework for trust management in edge-assisted VANETs. The proposed framework integrates mobility-aware trust inference, asynchronous
DAG validation, and edge-assisted partial trust synchronization to improve trust reliability and communication efficiency. In particular, the trust model jointly considers communication reliability, forwarding behavior, relative mobility, contact duration, and topology stability for dynamic trust evaluation. Moreover, the DAG-based validation mechanism enables parallel transaction verification, reducing consensus delay compared with conventional chain-based...
Highly dynamic topology and unreliable vehicular behaviors remain major challenges for blockchain-enabled trust management in Vehicular Ad Hoc Networks (VANETs). Conventional blockchain schemes often suffer from excessive consensus latency, communication overhead, and limited scalability in dense vehicular environments. To address these limitations, this paper proposes a lightweight DAG-blockchain framework for trust management in edge-assisted VANETs. The proposed framework integrates mobility-aware trust inference, asynchronous
DAG validation, and edge-assisted partial trust synchronization to improve trust reliability and communication efficiency. In particular, the trust model jointly considers communication reliability, forwarding behavior, relative mobility, contact duration, and topology stability for dynamic trust evaluation. Moreover, the DAG-based validation mechanism enables parallel transaction verification, reducing consensus delay compared with conventional chain-based blockchain architectures. Simulation results show that the proposed framework achieves
approximately 93.7% trust accuracy and 94.5% malicious vehicle detection rate under dense VANET scenarios while reducing communication latency and signaling overhead compared with PBFT-based blockchain and conventional reputationbased trust schemes