aspg-2-4038-1791417275
20261007235435
American Scientific Publishing Group
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American Scientific Publishing Group
Journal of Cybersecurity and Information Management
JCIM
2769-7851
2690-6775
2026
17
2
Feature Selection Techniques in Intrusion Detection Systems: A Review
Ahmad
Salim
Middle Technical University, Iraq
Obaid
Salim
General Directorate of Education Anbar, 31001, Iraq
Omar Muthanna
Khudhur
Department of Computer Engineering Techniques, College of Technical Engineering, University of Al Maarif, Al Anbar, 31001, Iraq
Shokhan M.
Al-Barzinji
Department of Computer Networks Systems, College of Computer Science and Information Technology, University of Anbar, Ramadi, Iraq
Farah Maath
Jasem
College of Computer Science and Information Technology, University of Anbar, Anbar, Iraq
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Intrusion detection has garnered significant attention as researchers strive to develop sophisticated models characterized by their high accuracy levels. However, the persistent challenge lies in creating reliable and effective intrusion detection systems capable of managing vast datasets under dynamic, real-time conditions. The effectiveness of such systems largely depends on the chosen detection methodologies, specifically the feature selection processes and the application of machine learning techniques. This paper offers a comprehensive review of feature selection methods employed in the realm of intrusion detection research. It examines various dimensionality reduction strategies, followed by a systematic classification of feature selection techniques to assess their impact on the training phase and subsequent detection efficacy. The focus was on the wrapper, filter feature selection methods, where the methods used were analysed, and their strengths and weaknesses were revealed. The identification and selection of the most pertinent features have been shown to significantly enhance the detection performance, not only in terms of accuracy but also in reducing computational demands, underscoring its critical importance in the architecture of intrusion detection systems.
2026
97
112
4038
https://creativecommons.org/licenses/by/4.0/
10.54216/JCIM.170208
https://www.americaspg.com/journal/2/article/4038
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https://www.americaspg.com/storage/51756407183.pdf