Article: A detailed analysis of public industrial control system datasets Journal: International Journal of Security and Networks (IJSN) 2023 Vol.18 No.4 pp.245 - 263 Abstract: A wide range of critical infrastructures such as power systems, water distribution systems, gas pipelines, and others are controlled and monitored using industrial control systems (ICSs). Recently, security attacks against ICSs are increasing at an alarming rate. These systems cannot afford to lose the availability of service; a cyber-attack can cause catastrophic damage. Intrusion detection systems (IDSs) are the first defence line against such attacks. To develop an effective IDS, a well-designed dataset is a must. In this paper, we present a detailed analysis of public intrusion datasets for ICSs. Focusing on the way security researchers used them to develop an IDS, their results, and the effect of the dataset's drawbacks. We performed exploratory data analysis (EDA), principal component analysis (PCA), and binary classification using random forest (RF) model. We believe this analysis will help the developers of the next generation of ICS-related IDSs. Inderscience Publishers - linking academia, business and industry through research

Title: A detailed analysis of public industrial control system datasets

Authors: Asaad Balla Babiker; Mohamed Hadi Habaebi; Sinil Mubarak; Md. Rafiqul Islam

Addresses: Department of Electrical and Computer Engineering, International Islamic University Malaysia, Kuala Lumpur, 53100, Malaysia ' Department of Electrical and Computer Engineering, International Islamic University Malaysia, Kuala Lumpur, 53100, Malaysia ' Department of Electrical and Computer Engineering, International Islamic University Malaysia, Kuala Lumpur, 53100, Malaysia ' Department of Electrical and Computer Engineering, International Islamic University Malaysia, Kuala Lumpur, 53100, Malaysia

Abstract: A wide range of critical infrastructures such as power systems, water distribution systems, gas pipelines, and others are controlled and monitored using industrial control systems (ICSs). Recently, security attacks against ICSs are increasing at an alarming rate. These systems cannot afford to lose the availability of service; a cyber-attack can cause catastrophic damage. Intrusion detection systems (IDSs) are the first defence line against such attacks. To develop an effective IDS, a well-designed dataset is a must. In this paper, we present a detailed analysis of public intrusion datasets for ICSs. Focusing on the way security researchers used them to develop an IDS, their results, and the effect of the dataset's drawbacks. We performed exploratory data analysis (EDA), principal component analysis (PCA), and binary classification using random forest (RF) model. We believe this analysis will help the developers of the next generation of ICS-related IDSs.

Keywords: intrusion detection system; IDS; industrial control system; ICS; datasets; cyber security; information security.

DOI: 10.1504/IJSN.2023.135511

International Journal of Security and Networks, 2023 Vol.18 No.4, pp.245 - 263

Received: 21 Jun 2022
Accepted: 27 Jun 2023
Published online: 15 Dec 2023 *

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Title: A detailed analysis of public industrial control system datasets

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