Toward Enhancing Security in Intelligent Transportation: A Simulation-Based Approach

This study undertakes a comprehensive examination within the dynamic framework of an urban setting, employing the SUMO simulation testbed for the city of Bologna, Italy, as a realistic traffic simulation model. This study uses a hybrid methodology that integrates the SUMO, OMNeT++, and VEINS framework to simulate communication within vehicle networks. The main emphasis is examining the different types of attacks that could happen on VANET network through various messages facilitated by the IEEE 802.11p protocol / WAVE (Wireless Access in vehicular Environments) standard. The primary objective of this simulation-based study is to improve vehicular network security by leveraging the inherent benefits of using WAVE standard messages, applying and analyzing techniques to detect intrusions in the network. We tested our simulation performance by applying a statistical threshold model for anomaly detection on the data generated from the simulation. Although the data was not enough for training, our goal was to test the possibility of simulating various types of attacks to generate big data that machine learning models can train in the future. This study highlights the importance of practical and realistic simulations, highlighting the importance of the IEEE 802.11p protocol and the WAVE standard in vehicular communication.