Intelligent Connected Vehicle Intrusion Detection and Mitigation: An Analysis of Explainable AI | |
---|---|
Author | |
Abstract |
IoT and AI created a Transportation Management System, resulting in the Internet of Vehicles. Intelligent vehicles are combined with contemporary communication technologies (5G) to achieve automated driving and adequate mobility. IoV faces security issues in the next five (5) areas: data safety, V2X communication safety, platform safety, Intermediate Commercial Vehicles (ICV) safety, and intelligent device safety. Numerous types of AI models have been created to reduce the outcome infiltration risks on ICVs. The need to integrate confidence, transparency, and repeatability into the creation of Artificial Intelligence (AI) for the safety of ICV and to deliver harmless transport systems, on the other hand, has led to an increase in explainable AI (XAI). Therefore, the space of this analysis protected the XAI models employed in ICV intrusion detection systems (IDSs), their taxonomies, and available research concerns. The study s findings demonstrate that, despite its relatively recent submission to ICV, XAI is a potential explore area for those looking to increase the net effect of ICVs. The paper also demonstrates that XAI s greater transparency will help it gain acceptance in the vehicle industry. |
Year of Publication |
2024
|
Date Published |
aug
|
URL |
https://ieeexplore.ieee.org/document/10704143
|
DOI |
10.1109/ICETCI62771.2024.10704143
|
Google Scholar | BibTeX | DOI |