A Comprehensive Exploration of AI Based Approaches for Enhancing Security and Routing in VANET

An example of a non-infrastructure system is a vehicle ad hoc network (VANET). Vehicle data sharing for traffic analysis and security is made possible by the network. This network's information transmission is time-sensitive, necessitating a solid and quick network connection. Because to its wireless ad hoc structure, VANET satisfies this criteria, regardless security issues. This network's most vibrant connections, sensitive info exchange, and time-bound nature makes it an appealing target for attackers. The study here describes the VANET literature survey, with a focus on vulnerabilities and the challenges associated with them. Paper discusses VANET layout, safety ethics, attack aspects, and characteristics of likely VANET attacks, as well as some remedies based on swarm based optimization techniques and machine learning for secure and energy effective routing. Paper also compares the results of some state of art work done and it has been found that selection of appropriate machine learning technique and optimization approach are crucial to VANETS security and efficient routing. In summary, this paper thoroughly investigates the VANET system as a whole as well as its applications along with analysis of potential remedies and security measures for guaranteeing safe and effective communication in VANETs.