Hybrid intrusion detection system based on Random forest, decision tree and Multilayer Perceptron (MLP) algorithms
Author:
Affiliation:
1. Ibn Tofail University,National School of Applied Sciences,Kenitra,Morocco
2. ENSIAS University Mohammed V Rabat,Morocoo
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10322877/10322879/10322983.pdf?arnumber=10322983
Reference25 articles.
1. Analyzing ML-Based IDS over Real-Traffic
2. An Improved Intrusion Detection Algorithm Based on GA and SVM
3. Comparative research on network intrusion detection methods based on machine learning
4. Comparative Analysis of ML Classifiers for Network Intrusion Detection
5. Impact of Gradient Ascent and Boosting Algorithm in Classification
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2. Enhancing Intrusion Detection Systems Using Machine Learning Classifiers on the CSE-CIC-IDS2018 Dataset;2024 11th International Conference on Wireless Networks and Mobile Communications (WINCOM);2024-07-23
3. BT Diagnosis and Segmentations using Designing of Ontological Framework;2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE);2024-05-14
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