The vehicular networks constructed by interconnected vehicles and transportation
infrastructure are vulnerable to cyber-intrusions due to the expanded use of software and the …

The large amount of driving data can help intelligent vehicles make decisions to drive safely,
improve vehicular services and enhance driving experience. In traditional vehicular …

As a novel computing paradigm, multiaccess edge computing (MEC) migrates computing
and storage capabilities to edge nodes of the network to meet the requirements of executing …

The present work aims to improve the communication security of Internet of Vehicles (IoV)
nodes in intelligent transportation through studying the safety of IoV in smart transportation …

The Internet of vehicles (IoV) is increasingly being used to realize the vision of intelligent
transportation systems with the rapid development of computation and communication …

Message exchange among vehicles plays an important role in ensuring road safety.
Emergency message dissemination is usually carried out by broadcasting. However, high …

Federated learning (FL) is a distributed machine learning approach that can achieve the
purpose of collaborative learning from a large amount of data that belong to different parties …

Vehicular edge computing (VEC) extends edge computing to vehicular networks by
exploiting computation resources of vehicles to offload tasks from other vehicles and …

The dynamic environment due to traffic mobility and wireless communication from/to
vehicles make identity authentication and trust management for privacy preservation based …

Data sharing and privacy securing present extensive opportunities and challenges in
vehicular network. This paper introducestrust access authentication scheme'as a …