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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 2/2020

06.07.2020

Towards the Development of Realistic DoS Dataset for Intelligent Transportation Systems

verfasst von: Rabah Rahal, Abdelaziz Amara Korba, Nacira Ghoualmi-Zine

Erschienen in: Wireless Personal Communications | Ausgabe 2/2020

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Abstract

Vehicular ad-hoc networks (VANETs) present security vulnerabilities, which make them prone to diverse cyberattacks. Denial of Service (DoS) is one of the most prevalent and severe cyberattack that targets VANETs. To tackle this cyberattack and mitigate its effect, intrusion detection systems need to be developed. To this end, a realistic and representative dataset is essential to train and validate the systems. This paper proposes a new dataset, VDoS-LRS, which includes legitimate and simulated vehicular network traffic, along with different types of DoS cyberattack. We also present a realistic testbed environment instead of simulators, taking into consideration different environments (urban, highway and rural). In addition, we explore a wide range of traffic features for detecting and classifying vehicular traffic. We evaluate the reliability of the VDoS-LRS dataset using different machine learning algorithms for forensics purposes. The experimental results showed that it is possible to detect effectively different types of DoS cyberattack within diverse environments.
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Metadaten
Titel
Towards the Development of Realistic DoS Dataset for Intelligent Transportation Systems
verfasst von
Rabah Rahal
Abdelaziz Amara Korba
Nacira Ghoualmi-Zine
Publikationsdatum
06.07.2020
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 2/2020
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-020-07635-1

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