Integrating Blockchain and Machine Learning with 6G for Autonomous Vehicle Communication: Achieving Secure, Transparent, and Scalable V2X Networks

Abstract

The rapid evolution of autonomous vehicle technology necessitates robust communication frameworks to ensure safety, reliability, and scalability in vehicular networks. Blockchain and machine learning technologies integrated with 6G networks develop a secure, transparent, and scalable Vehicle-to-Everything communication system. Leveraging ultra-low latency, massive connectivity and enhanced bandwidth, this framework addresses challenges including data integrity, real-time decision making and network scalability. Blockchain ensures secure and tamper-proof data exchange among vehicles, infrastructure and edge devices. Machine learning algorithms enhance predictive capabilities for route optimization, collision avoidance and traffic management. This synergy strengthens through a decentralized edge computing model enabling real-time data processing and reducing central network bottlenecks. Experimental evaluations on a simulated 6G-V2X testbed demonstrate significant improvements in network performance, security metrics and decision making accuracy compared to traditional frameworks. This establishes a foundational approach achieving trust, transparency and scalability in next generation autonomous vehicle networks. Insights provide for future deployments in intelligent, secure and efficient transportation ecosystems and smart cities. The proposed system serves as a pivotal step towards realizing communication infrastructures aligning with emerging demands.