A Wrapper Feature Selection Based Hybrid Deep Learning Model for DDoS Detection in a Network with NFV Behaviors
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s11277-023-10775-9.pdf
Reference41 articles.
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3. Banitalebi Dehkordi, A., Soltanaghaei, M., & Boroujeni, F. Z. (2021). The DDoS attacks detection through machine learning and statistical methods in SDN. The Journal of Supercomputing, 77(3), 2383–2415.
4. Dong, S., & Sarem, M. (2019). DDoS attack detection method based on improved KNN with the degree of DDoS attack in software-defined networks. IEEE Access, 8, 5039–5048.
5. Haider, S., Akhunzada, A., Mustafa, I., Patel, T. B., Fernandez, A., Choo, K. K., & Iqbal, J. (2020). A deep CNN ensemble framework for efficient DDoS attack detection in software defined networks. IEEE Access, 8, 53972–53983.
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