Secure Edge Computing in Intelligent Vehicular Communication Networks

The accelerated growth of Intelligent Vehicular Communication Networks (IVCNs) promises revolutionary opportunities in enhancing road safety, traffic flow, and general user experience. But with it comes the monumental challenge of ensuring data security and privacy, especially as edge computing becomes a reality in processing information close to the vehicle and infrastructure. This work explores safe edge computing in IVCNs through analysis of their special security needs—i.e., real-time processing, scalability, low latency—and their vulnerabilities as inherently decentralized network constructs. We also review edge computing models and survey the reinforcement of security mechanisms through encryption, authentication, intrusion detection, blockchain technology, machine learning, and trusted execution environments. From these findings, we present here a complete scheme that combines security, efficiency, and scalability in secure edge computing for IVCNs. With this contribution, we present future research directions as well as deployment strategies, setting the stage finally for safer, more efficient automotive communication systems.