Blockchain-Powered Privacy Preservation and Attack Mitigation for 6g-Connected Vehicular Clouds

The transition toward sixth-generation (6G) wireless communication is expected to significantly expand the scale, intelligence, and connec-‎tivity of vehicular cloud networks, while simultaneously intensifying their exposure to sophisticated cyber threats and privacy risks. Contin-‎uous exchange of vehicular telemetry, combined with ultra-low-latency communication and high mobility, renders conventional centralized ‎security and intrusion detection mechanisms inadequate. This paper presents a decentralized, privacy-aware security methodology for 6G-‎enabled vehicular cloud environments that integrates dynamic trust evaluation, federated anomaly detection, and blockchain-based enforce-‎ment.‎ The proposed approach employs adaptive trust modeling to continuously assess vehicular behavior, federated learning to enable collabora-‎tive anomaly detection without disclosing raw data, and a lightweight Proof-of-Trust consensus mechanism to ensure low-latency, verifiable ‎decision-making. Automated mitigation is enforced through smart contracts, enabling rapid response and accountability without centralized ‎control. The methodology is evaluated using three widely adopted benchmark datasets—CIC-IDS2017, TON_IoT, and N-BaIoT—that ‎cover volumetric attacks, stealthy intrusions, and coordinated botnet behavior.‎ Experimental results demonstrate detection rates exceeding 95% across all datasets, with false-positive rates of nearly 1%. End-to-end detec-‎tion-to-mitigation latency remains below 20 ms under high vehicular density, satisfying 6G ultra-reliable low-latency communication re-‎quirements. A comparative analysis reveals that the proposed approach outperforms traditional signature-based and learning-based intrusion ‎detection systems in terms of accuracy, scalability, and enforcement capability, while maintaining data privacy through federated learning ‎and differential privacy mechanisms.‎ These results confirm that decentralized trust management, privacy-preserving intelligence, and automated blockchain enforcement can be ‎jointly realized in 6G vehicular cloud systems. The proposed methodology provides a practical, scalable foundation for securing next-‎generation intelligent transportation infrastructure against evolving cyber threats‎.