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article

Review: The use of computational intelligence in intrusion detection systems: A review

Authors:

Shelly Xiaonan Wu,

Wolfgang BanzhafAuthors Info & Claims

Applied Soft Computing, Volume 10, Issue 1

Pages 1 - 35

https://doi.org/10.1016/j.asoc.2009.06.019

Published: 01 January 2010 Publication History

Abstract

Intrusion detection based upon computational intelligence is currently attracting considerable interest from the research community. Characteristics of computational intelligence (CI) systems, such as adaptation, fault tolerance, high computational speed and error resilience in the face of noisy information, fit the requirements of building a good intrusion detection model. Here we want to provide an overview of the research progress in applying CI methods to the problem of intrusion detection. The scope of this review will encompass core methods of CI, including artificial neural networks, fuzzy systems, evolutionary computation, artificial immune systems, swarm intelligence, and soft computing. The research contributions in each field are systematically summarized and compared, allowing us to clearly define existing research challenges, and to highlight promising new research directions. The findings of this review should provide useful insights into the current IDS literature and be a good source for anyone who is interested in the application of CI approaches to IDSs or related fields.

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Singh APrakash JKumar GJain PAmbati L(2024)Intrusion Detection SystemJournal of Database Management10.4018/JDM.33827635:1(1-25)Online publication date: 21-Feb-2024
https://dl.acm.org/doi/10.4018/JDM.338276
Li BXu ZWang X(2024)Computational intelligence and its dynamic development: statistical exploration, comprehensive evaluation and prospect expansionSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-024-09789-728:17-18(9371-9386)Online publication date: 1-Sep-2024
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Review: The use of computational intelligence in intrusion detection systems: A review
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
  2. Machine learning
    1. Learning paradigms
      1. Supervised learning
    2. Machine learning approaches

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cover image Applied Soft Computing

Applied Soft Computing Volume 10, Issue 1

January, 2010

361 pages

ISSN:1568-4946

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Singh APrakash JKumar GJain PAmbati L(2024)Intrusion Detection SystemJournal of Database Management10.4018/JDM.33827635:1(1-25)Online publication date: 21-Feb-2024
https://dl.acm.org/doi/10.4018/JDM.338276
Li BXu ZWang X(2024)Computational intelligence and its dynamic development: statistical exploration, comprehensive evaluation and prospect expansionSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-024-09789-728:17-18(9371-9386)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1007/s00500-024-09789-7
Saurabh PVerma B(2023)Negative selection in anomaly detection—A surveyComputer Science Review10.1016/j.cosrev.2023.10055748:COnline publication date: 1-May-2023
https://dl.acm.org/doi/10.1016/j.cosrev.2023.100557
Wei WChen YLin QJi JWong KLi J(2023)Multi-objective evolving long–short term memory networks with attention for network intrusion detectionApplied Soft Computing10.1016/j.asoc.2023.110216139:COnline publication date: 1-May-2023
https://dl.acm.org/doi/10.1016/j.asoc.2023.110216
Alsenani TAyon SYousuf SAnik FChowdhury M(2023)Intelligent feature selection model based on particle swarm optimization to detect phishing websitesMultimedia Tools and Applications10.1007/s11042-023-15399-682:29(44943-44975)Online publication date: 1-Dec-2023
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Deveci AYilmaz SSen S(2023)Evolving Lightweight Intrusion Detection Systems for RPL-Based Internet of ThingsApplications of Evolutionary Computation10.1007/978-3-031-30229-9_12(177-193)Online publication date: 12-Apr-2023
https://dl.acm.org/doi/10.1007/978-3-031-30229-9_12
Picek SJakobovic DWagner M(2022)Evolutionary computation and machine learning in securityProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3520304.3534087(1572-1601)Online publication date: 9-Jul-2022
https://dl.acm.org/doi/10.1145/3520304.3534087
Macas MWu CFuertes W(2022)A survey on deep learning for cybersecurityComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2022.109032212:COnline publication date: 20-Jul-2022
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Smara MAliouat MHarous SPathan A(2022)Robustness improvement of component-based cloud computing systemsThe Journal of Supercomputing10.1007/s11227-021-04054-278:4(4977-5009)Online publication date: 1-Mar-2022
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Sah GBanerjee SSingh S(2022)Intrusion detection system over real-time data traffic using machine learning methods with feature selection approachesInternational Journal of Information Security10.1007/s10207-022-00616-422:1(1-27)Online publication date: 6-Oct-2022
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