Subject Areas : Pattern Recognition
Chetan Gupta 1 , Amit Kumar 2 , Neelesh Kumar Jain 3
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Keywords:
Abstract :
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28. Maseno, E.M., Wang, Z. “Hybrid wrapper feature selection method based on genetic algorithm and extreme learning machine for intrusion detection”. – In: Journal of Big Data, February 2024, Volume 11, article number 24, https://doi.org/10.1186/s40537-024-00887-9.
29. Hamdi, N. “Federated learning-based intrusion detection system for Internet of Things”. – In: International Journal of Information Security. July 2023, Volume 22, pages 1937–1948. https://doi.org/10.1007/s10207-023-00727-6.
30. Akhtar, M.A., Qadri, S.M.O., Siddiqui, M.A. et al. “Robust genetic machine learning ensemble model for intrusion detection in network traffic”. – In: Scientific Reports. October 2023, Volume 13, article number 17227. https://doi.org/10.1038/s41598-023-43816-1.
31. Talukder, M.A., Islam, M.M., Uddin, M.A. et al. “Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction”. – In: Journal of Big Data. February 2024, Volume 11, article number 33. https://doi.org/10.1186/s40537-024-00886-w.
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35. Sumaiya Thaseen Ikram, Aswani Kumar Cherukuri, Babu Poorva, Pamidi Sai Ushasree, et al. “Anomaly Detection Using XGBoost Ensemble of Deep Neural Network Models”. – In: Cybernetics and Information Technologies. Sep. 2021. Volume 24, Issue 2. https://doi.org/10.2478/cait-2021-0037.
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37. Sarwat Ejaz, Umara Noor and Zahid Rashid. “Visualizing Interesting Patterns in Cyber Threat Intelligence Using Machine Learning Techniques”. – In: Cybernetics and Information Technologies. June 2022. Volume 22, Issue 2. https://doi.org/10.2478/cait-2022-0019.