Tree-based Intelligent Intrusion Detection System in Internet of Vehicles

Authors: Li Yang, Abdallah Moubayed, Ismail Hamieh, Abdallah Shami
Published: 2019-10-18 | Updated: 2022-10-05

Source: https://arxiv.org/abs/1910.08635

PDF: https://arxiv.org/pdf/1910.08635

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モデルアンサンブル 特徴重要度分析 サイバー脅威

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Abstract

The use of autonomous vehicles (AVs) is a promising technology in Intelligent Transportation Systems (ITSs) to improve safety and driving efficiency. Vehicle-to-everything (V2X) technology enables communication among vehicles and other infrastructures. However, AVs and Internet of Vehicles (IoV) are vulnerable to different types of cyber-attacks such as denial of service, spoofing, and sniffing attacks. In this paper, an intelligent intrusion detection system (IDS) is proposed based on tree-structure machine learning models. The results from the implementation of the proposed intrusion detection system on standard data sets indicate that the system has the ability to identify various cyber-attacks in the AV networks. Furthermore, the proposed ensemble learning and feature selection approaches enable the proposed system to achieve high detection rate and low computational cost simultaneously.