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Bharathyalagi / repository
Hybrid WCGAN-ACGAN framework for balanced network intrusion detection on NSL-KDD and UNSW-NB15 datasets using XGBoost, Decision Trees, CNN, and AutoGluon classifiers
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This repository contains implementations of GAN-based synthetic data generation and classifiers for intrusion detection using NSL-KDD and UNSW-NB15 datasets.
CNN/ : CNN experiments for both datasets.nsl-kdd/ : GAN + classifiers experiments for NSL-KDD dataset.unsw-nb15/ : GAN + classifiers experiments for UNSW-NB15 dataset.Refer to individual folder README.md files for dataset-specific instructions.
hybrid-gan-ids/
├── CNN/
│ ├── cnn.ipynb
│ └── README.md
│
├── nsl-kdd/
│ ├── acgan+decision-tree/
│ ├── wcgan+decision-tree/
│ ├── wcgan+xgboost/
│ └── README.md
│
├── unsw-nb15/
│ ├── acgan+decision-tree/
│ ├── wcgan+decision-tree/
│ ├── wcgan+xgboost/
│ └── README.md
│
└── README.md
This project is licensed under the MIT License - see the LICENSE file for details.
This is a large project, so it might be confusing at first. Please check the README.md files in each folder carefully to understand the workflow and structure.