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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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An Anomaly Detection Technique for Deception.pdf | 515.77 kB | Adobe PDF | View/Open |
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