GitHub / Western-OC2-Lab / Intrusion-Detection-System-Using-Machine-Learning
Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
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PURL: pkg:github/Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning
Stars: 510
Forks: 132
Open issues: 0
License: mit
Language: Jupyter Notebook
Size: 17.7 MB
Dependencies parsed at: Pending
Created at: about 4 years ago
Updated at: 16 days ago
Pushed at: almost 2 years ago
Last synced at: 11 days ago
Topics: autonomous-vehicles, bayesian-optimization, catboost, cicids2017, cyber-security, decision-tree, ensemble-learning, hpo, hyperparameter-optimization, intrusion-detection, intrusion-detection-system, kmeans, lightgbm, machine-learning, network-security, python-examples, random-forest, stacking, xgboost