Research progress on autonomous driving security technology for vehicle-road-cloud collaboration

Abstract

With the advancement of edge intelligence technology and the acceleration of urbanization, intelligent transportation systems (ITS) have experienced rapid development. Vehicle-road-cloud (VRC) collaboration was enabled through the coordinated sharing of vehicle-to-vehicle (V2V), vehicle-to-road (V2R), and vehicle-to-cloud (V2C) data in the Internet of vehicles, thereby constructing a more efficient cooperative intelligent transportation system (C-ITS). However, numerous security threats in VRC collaboration were found to severely impede the development of cooperative autonomous driving. The development status of VRC collaboration was first summarized, and the history of autonomous driving and the VRC-based autonomous driving environment were elaborated. Subsequently, attacks and security defense technologies in VRC collaboration were systematically categorized into two types: classical information security mechanisms and defense technologies, which were detailed from five aspects—information availability, integrity, confidentiality, authenticity, and non-repudiation; and machine learning-based security threats and defense technologies, which were analyzed from both centralized and distributed perspectives. Finally, future development directions and research priorities of VRC collaborative security technologies were forecasted, primarily covering federated learning, blockchain technology, secure multi-party computation, zero-knowledge proof, and differential privacy technology.