A New Random Forest and Support Vector Machine-based Intrusion Detection Model in Networks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Engineering (miscellaneous)
Link
https://link.springer.com/content/pdf/10.1007/s40009-023-01223-0.pdf
Reference20 articles.
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3. Diaz-Verdejo Jesus E, Pedro Garcia-Teodoro, Muñoz P, Maciá-Fernández G, De Toro F (2007) A snort-based approach for the development and deployment of hybrid IDS. IEEE Latin Am Trans 5(6):386–392
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2. IDRandom-Forest: Advanced Random Forest for Real-Time Intrusion Detection;IEEE Access;2024
3. A Comparative Analysis on Ensemble Learning and Deep Learning Based Intrusion Detection Systems over the NCC2 Dataset;Advances in Intelligent Systems and Computing;2024
4. Novel Class Probability Features for Optimizing Network Attack Detection With Machine Learning;IEEE Access;2023
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