AI-Driven Digital Twin Frameworks For Next-Gen 6G V2X Security Solutions

Arjun M Nair , Akhija Lakshmi R

6G, Internet of Vehicles (IoV), Vehicle-to- Everything (V2X), Digital Twin (DT), Cybersecurity, Intrusion Detection, Trust Management, Authentication, Vehicle-to-Grid (V2G), Cyber-Twin, Open RAN, Federated Learning, Blockchain, Autonomous Driving, Smart Transportation Systems, Low Latency, Scalability, Resilience.

The arrival of sixth-generation (6G) networks is set to change the Internet of Vehicles (IoV) and Vehicle-to-Everything (V2X) communication. It will provide ultra-low latency, high reliability, and smooth connectivity for future self-driving cars and smart transportation systems. With more artificial intelli- gence (AI), edge computing, and fast communication, IoV will be the foundation of next-generation mobility services. However, the open, dynamic, and diverse nature of vehicle networks makes them very vulnerable to various cyber threats. Attacks such as Sybil, spoofing, denial-of-service (DoS), replay, and data manipulation can undermine trust, disrupt services, and even put passenger safety at risk. Traditional cryptography and security protocols are somewhat effective but often face problems with scalability, high overhead, and limited flexibility in highly mobile and resource-limited settings. Digital Twin (DT) technology has emerged as a promising way to overcome these limitations. It creates smart virtual replicas of vehicles, networks, and environments. These digital counterparts allow real-time monitoring, detect problems, and provide predictive security defense. Recent advancements show the effectiveness of DT-driven security methods. Cyber-Twin- based intrusion detection improves the recognition of anomalies and allows for flexible countermeasures. In the same way, DT- powered data sharing in Open RAN boosts data confidentiality and integrity while cutting down on communication delays. Trust management strategies based on DTs help evaluate vehicle interactions, ensuring reliable decision-making and detection of harmful nodes. Additionally, the combination of federated learn- ing with blockchain technology offers decentralized, privacy- protecting, and tamper-resistant security solutions. This ap- proach helps address issues like data poisoning and reliance on central authorities. Collectively, DT-enabled frameworks improve detection accu- racy, reduce latency, increase scalability, and boost resilience against complex cyberattacks. These advancements show the transformative potential of DTs in securing 6G-enabled vehicular networks. They are essential for creating safe, efficient, and intelligent transportation systems.

Volume 13 Issue 10, October-2025

Pages : c430-c434