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Tree-Based Intelligent Intrusion Detection System in Internet of Vehicles

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TLDR
An intelligent intrusion detection system (IDS) is proposed based on tree-structure machine learning models that has the ability to identify various cyber-attacks in the AV networks and can achieve high detection rate and low computational cost simultaneously.
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.

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Citations
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Journal ArticleDOI

I and i

Kevin Barraclough
- 08 Dec 2001 - 
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
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On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice

TL;DR: This survey paper will help industrial users, data analysts, and researchers to better develop machine learning models by identifying the proper hyper-parameter configurations effectively and introducing several state-of-the-art optimization techniques.
Journal ArticleDOI

Novel Deep Learning-Enabled LSTM Autoencoder Architecture for Discovering Anomalous Events From Intelligent Transportation Systems

TL;DR: A deep learning-based Intrusion Detection System (IDS) for ITS, in particular, to discover suspicious network activity of In-Vehicles Networks (IVN), vehicles to vehicles communications and vehicles to infrastructure (V2I) networks.
Journal ArticleDOI

MTH-IDS: A Multi-Tiered Hybrid Intrusion Detection System for Internet of Vehicles

TL;DR: In this article, a multi-tiered hybrid IDS was proposed to detect both known and unknown attacks on vehicular networks, which can detect various types of known attacks with 99.99% accuracy on the CAN-intrusion-dataset representing the intra-vehicle network data.
Journal ArticleDOI

Systematic ensemble model selection approach for educational data mining

TL;DR: This work proposes a systematic approach based on Gini index and p -value to select a suitable ensemble learner from a combination of six potential machine learning algorithms.
References
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Efficient Intrusion Detection With Bloom Filtering in Controller Area Networks

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Proceedings ArticleDOI

Machine Learning for Performance-Aware Virtual Network Function Placement

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Proceedings ArticleDOI

DNS Typo-Squatting Domain Detection: A Data Analytics a Machine Learning Based Approach

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