An Anomaly Detection Technique for Deception Attacks in Industrial Control Systems
Anomaly detection; Big data; Commercial off-the-shelf; Computer crime; Intrusion detection; Learning systems; Network security; SCADA systems; Terrorism; Catastrophic consequences; Commercial off-the-shelf products; Deception Attack; Industrial control systems; Intrusion Detection Systems; Intrusion...
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Institute of Electrical and Electronics Engineers Inc.
2023
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| _version_ | 1833412830880071680 |
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| author | Qassim Q. Ahmad A.R. Ismail R. Abu Bakar A. Abdul Rahim F. Mokhtar M.Z. Ramli R. Mohd Yusof B. Mahdi M.N. |
| author2 | 36613541700 |
| author_facet | 36613541700 Qassim Q. Ahmad A.R. Ismail R. Abu Bakar A. Abdul Rahim F. Mokhtar M.Z. Ramli R. Mohd Yusof B. Mahdi M.N. |
| author_sort | Qassim Q. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Anomaly detection; Big data; Commercial off-the-shelf; Computer crime; Intrusion detection; Learning systems; Network security; SCADA systems; Terrorism; Catastrophic consequences; Commercial off-the-shelf products; Deception Attack; Industrial control systems; Intrusion Detection Systems; Intrusion detection technologies; National infrastructure; SCADA; Intelligent control |
| format | Conference Paper |
| id | my.uniten.dspace-24663 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | my.uniten.dspace-246632023-05-29T15:25:37Z An Anomaly Detection Technique for Deception Attacks in Industrial Control Systems Qassim Q. Ahmad A.R. Ismail R. Abu Bakar A. Abdul Rahim F. Mokhtar M.Z. Ramli R. Mohd Yusof B. Mahdi M.N. 36613541700 35589598800 15839357700 35178991300 57350579500 36544184200 57191413657 57215353012 56727803900 Anomaly detection; Big data; Commercial off-the-shelf; Computer crime; Intrusion detection; Learning systems; Network security; SCADA systems; Terrorism; Catastrophic consequences; Commercial off-the-shelf products; Deception Attack; Industrial control systems; Intrusion Detection Systems; Intrusion detection technologies; National infrastructure; SCADA; Intelligent control 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. Final 2023-05-29T07:25:37Z 2023-05-29T07:25:37Z 2019 Conference Paper 10.1109/BigDataSecurity-HPSC-IDS.2019.00057 2-s2.0-85072773110 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072773110&doi=10.1109%2fBigDataSecurity-HPSC-IDS.2019.00057&partnerID=40&md5=92b0e3536c49703f22dd007dad4d1512 https://irepository.uniten.edu.my/handle/123456789/24663 8819478 267 272 Institute of Electrical and Electronics Engineers Inc. Scopus |
| spellingShingle | Qassim Q. Ahmad A.R. Ismail R. Abu Bakar A. Abdul Rahim F. Mokhtar M.Z. Ramli R. Mohd Yusof B. Mahdi M.N. An Anomaly Detection Technique for Deception Attacks in Industrial Control Systems |
| title | An Anomaly Detection Technique for Deception Attacks in Industrial Control Systems |
| title_full | An Anomaly Detection Technique for Deception Attacks in Industrial Control Systems |
| title_fullStr | An Anomaly Detection Technique for Deception Attacks in Industrial Control Systems |
| title_full_unstemmed | An Anomaly Detection Technique for Deception Attacks in Industrial Control Systems |
| title_short | An Anomaly Detection Technique for Deception Attacks in Industrial Control Systems |
| title_sort | anomaly detection technique for deception attacks in industrial control systems |
| url_provider | http://dspace.uniten.edu.my/ |