A python-based Network Intusion Detection System, for every one.
Machine Learning - Network Intrusion Detection System
Anomaly-Based Network Intrusion Detection Using Ensemble Learning
Built a dual-model intrusion detection system using the NSL-KDD dataset. The binary model detects normal vs. malicious traffic, while the multiclass model classifies attacks as DoS, Probe, R2L, or U2R. Applied advanced preprocessing, dimensionality reduction, and ensemble methods (XGBoost, LightGBM, SVM) with recall focused cross-validation
Add a description, image, and links to the network-intrusion-detection-system topic page so that developers can more easily learn about it.
To associate your repository with the network-intrusion-detection-system topic, visit your repo's landing page and select "manage topics."