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Anomaly detection in ICS datasets with machine learning algorithms

Mubarak, Sinil and Habaebi, Mohamed Hadi and Islam, Md. Rafiqul and Abdul Rahman, Farah Diyana and Tahir, Mohammad (2021) Anomaly detection in ICS datasets with machine learning algorithms. Computer Systems Science and Engineering, 37 (1). pp. 33-46. ISSN 0267-6192

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An Intrusion Detection System (IDS) provides a front-line defense mechanism for the Industrial Control System (ICS) dedicated to keeping the process operations running continuously for 24 hours in a day and 7 days in a week. A well-known ICS is the Supervisory Control and Data Acquisition (SCADA) system. It supervises the physical process from sensor data and performs remote monitoring control and diagnostic functions in critical infrastructures. The ICS cyber threats are growing at an alarming rate on industrial automation applications. Detection techniques with machine learning algorithms on public datasets, suitable for intrusion detection of cyber-attacks in SCADA systems, as the first line of defense, have been detailed. The machine learning algorithms have been performed with labeled output for prediction classification. The activity traffic between ICS components is analyzed and packet inspection of the dataset is performed for the ICS network. The features of flow-based network traffic are extracted for behavior analysis with port-wise profiling based on the data baseline, and anomaly detection classification and prediction using machine learning algorithms are performed.

Item Type: Article (Journal)
Additional Information: 6727/88266
Uncontrolled Keywords: Industrial control system; SCADA; intrusion detection system; machine learning; anomaly detection
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Dr. Mohamed Hadi Habaebi
Date Deposited: 09 Feb 2021 08:31
Last Modified: 30 Jun 2021 15:47
URI: http://irep.iium.edu.my/id/eprint/88266

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