INTELLIGENT COMPUTING PARADIGMS FOR MISBEHAVIOUR DETECTION IN VEHICULAR NETWORKS:AN INVESTIGATION STUDY

Vehicular Ad Hoc Networks (VANETs) are integral to the development of Intelligent Transportation Systems (ITS), facilitating communication between vehicles and infrastructure to enhance road safety, traffic management, and overall driving experience. However, the open and dynamic nature of these networks exposes them to various security threats, including misbehavior by malevolent hubs that can disrupt communication and compromise safety. The literature survey here provides a comprehensive outline of recent advancements in misbehavior detection techniques in VANETs, focusing on various approaches such as machine learning, deep learning, and federated learning.