Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/13030
Title: An Anomaly Detection Technique for Deception Attacks in Industrial Control Systems
Authors: Qassim, Q. 
Ahmad, A.R. 
Ismail, R. 
Abu Bakar, A. 
Abdul Rahim, F. 
Mokhtar, M.Z. 
Ramli, R. 
Mohd Yusof, B. 
Mahdi, M.N. 
Issue Date: 2019
Abstract: The increasing interaction of modern industrial control systems (ICS) to the outside Internet world influences making these systems vulnerable to a wide range of cyber-attacks. Moreover, the utilisation of Commercial-off-the-Shelf (COTS) products, as well as open communication protocols, made them attractive targets to various threat agents including cyber-criminals, national-state, and cyber-terrorists. Given that, today's ICSs are deriving the most critical national infrastructures. Therefore, this raises tremendous needs to secure these systems against cyber-attacks. Intrusion detection technology has been considered as one of the most essential security precautions for ICS networks. It can effectively detect potential cyber-attacks and malicious activities and prevent catastrophic consequences. This paper puts forward a new method to detect malicious activities at the ICS net-works. © 2019 IEEE.
DOI: 10.1109/BigDataSecurity-HPSC-IDS.2019.00057
Appears in Collections:UNITEN Scholarly Publication

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