A Comparative Study of Machine Learning and Deep Learning Models for Intrusion Detection in ICS

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Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{184325,
        author = {Shantanu Kumar Suman and Ramakant Pal},
        title = {A Comparative Study of Machine Learning and Deep Learning Models for Intrusion Detection in ICS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {4},
        pages = {885-892},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=184325},
        abstract = {},
        keywords = {Intrusion detection, Industrial control systems, Benchmark ICS dataset, machine learning, deep learning, CNN, XGBoost, TabNet, class imbalance, SMOTE.},
        month = {September},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 12
  • Issue: 4
  • PageNo: 885-892

A Comparative Study of Machine Learning and Deep Learning Models for Intrusion Detection in ICS

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