Paper Title
Design and Evaluation of Intrusion Detection System for Vehicular Ad Hoc Networks Using Ton-Iot Dataset

Abstract
Technology has made tremendous changes in Communication and networking sector, from 1G to 5G., from a audio signal communication to multimedia distribution. With multiplying users of Automobile Industry, the security of human populace, environment pollution and societal overall health has taken a prime importance. Every part of vehicular transport system would be under one umbrella of control and monitoring. This seeks for better multimedia to connect enormous number of various devices requiring Device-to-Device(D2D) and Device-to-Infrastructure (D2I). Existing networking is becoming inadequate as communication technology paceing towards ultra-low latency, low cost and scalable, which has launched new paradigm in applications like, vehicular traffic, IoT devices, etc.. Many researches are being undertaken by telecom companies, universities with huge investment. Yet there are bottlenecks waiting to get better solutions. This work proposes to have in-depth study of security aspect of the vehicular traffic and suggest better, machine learning/AI, 5G-IoT based models and solution. Keywords - Machine Learning, Artificial Intelligence, VANET, Intrusion Detection System, ToN-IoT.