An Anomaly Detection Technique for Deception Attacks in Industrial Control Systems

被引:3
|
作者
Qassim, Q. S. [1 ]
Ahmad, A. R. [1 ,2 ]
Ismail, R. [1 ,2 ]
Bakar, Abu A. [1 ,2 ]
Rahim, Abdul F. [1 ,2 ]
Mokhtar, M. Z. [1 ,2 ]
Ramli, R. [1 ,2 ]
Mohd, Yusof B. [1 ]
Mahdi, Mohammed Najah [1 ]
机构
[1] Univ Tenaga Nas, Inst Informat & Comp Energy, Kajang 43000, Malaysia
[2] Univ Tenaga Nas, Coll Comp & Informat, Kajang 43000, Malaysia
关键词
Intrusion Detection System; SCADA; Deception Attack; Machine Learning; Industrial Control Systems;
D O I
10.1109/BigDataSecurity-HPSC-IDS.2019.00057
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:267 / 272
页数:6
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