Machine Learning Technique of Intrusion Detection System for Vehicular Ad Hoc Networks : An Analysis

A vehicular ad-hoc network (VANET) is a subset of mobile AD-NET that enables communication between automobiles and surrounding fixed equipment, which is often referred to as roadside equipment. The primary objective of VANET is to provide passenger comfort and safety. Each car will be equipped with a unique electronic gadget that will enable the formation of an ad hoc network and link the passengers. In order to reduce traffic congestion, assure safety, and preserve the environment, intelligent transport systems (ITS) combine computers, communications networks, sensors, location, and automation technologies that gather and create data. ITS also provides users with a variety of services and applications. Intrusion detection is one of the important security problems in today's scenario. A significant number of techniques have been developed to detect and prevent of instruction in the VANET based on machine learning approaches. This paper presents analysis of machine learning technique of intrusion detection system for vehicular ad hoc networks.