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Cyber attacks analysis and mitigation with machine learning techniques in ICS SCADA systems

Mubarak, Sinil and Habaebi, Mohamed Hadi and Abdul Rahman, Farah Diyana and Khan, Sheroz and Islam, Md. Rafiqul (2019) Cyber attacks analysis and mitigation with machine learning techniques in ICS SCADA systems. Journal of Advanced Research in Dynamical and Control Systems, 11 (1). pp. 180-188. ISSN 1943-023X

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Abstract

Supervisory control and data acquisition (SCADA) system is a computer based system implemented to control the physical processes which enhances the operational efficiency, cost reduction and energy consumption. It supervises physical process by collecting data from sensors and performs monitoring, data logging, alarm and diagnostic functions. The advancement in technology for connectivity in communication protocols has resulted the system to be more vulnerable to cyber-attacks. The classifications of various attacks along with the intrusions detection methods have been highlighted. Mitigation techniques such as honeypot simulation which helps in vulnerability assessment, along with machine learning algorithms, suitable for intrusion detection and prevention of cyber-attacks in SCADA systems has been detailed.

Item Type: Article (Journal)
Additional Information: 6727/71214
Uncontrolled Keywords: SCADA, ICS, Energy Security, Intrusion Detection System, Machine Learning
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Kulliyyah of Engineering
Depositing User: Dr. Mohamed Hadi Habaebi
Date Deposited: 22 Mar 2019 17:02
Last Modified: 22 Mar 2019 17:02
URI: http://irep.iium.edu.my/id/eprint/71214

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