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DGA Domain Detection System

中文版

Project Overview

This is a DGA (Domain Generation Algorithm) detection system based on RNN (Recurrent Neural Network). The system can automatically identify whether a domain name is maliciously generated by DGA.

Features

  • RNN model for domain classification
  • Real-time domain detection
  • Pre-trained model available
  • Training process visualization
  • High accuracy detection results

Dataset

The training dataset consists of two parts:

  • Malicious domains generated by DGA
  • Legitimate domains

You can download the complete dataset from Google Drive.

Requirements

  • Python 3.7+
  • PyTorch
  • pandas
  • matplotlib
  • scikit-learn

Installation

  1. Clone the repository
git clone https://github.com/yourusername/dga-detection.git
cd dga-detection
  1. Install dependencies
pip install -r requirements.txt
  1. Download the dataset and place it in the data directory

Usage

  1. Train the model
python main.py
  1. Predict domains
python predict.py

Project Structure

.
├── data/               # Data directory
├── main.py            # Main program
├── model.py           # Model definition
├── trainer.py         # Trainer
├── predict.py         # Prediction script
├── utils.py           # Utility functions
└── data_loader.py     # Data loader

License

MIT License

Contributing

Pull requests and issues are welcome.

Contact

Please submit an issue if you have any questions.