CyberAttackDetection-Python

Overview

CyberAttackDetection-Python is a project aimed at detecting cyber attacks using machine learning models. This repository contains code for data preprocessing, model training, evaluation, and utilities.

Directory Structure

CyberAttackDetection-Python/
├── .github/
│   └── workflows/
│       └── ci.yml
├── models/
│   └── random_forest_model.pkl
│   └── simple_nn_model.pth
├── data/
│   └── raw_data.csv
│   └── processed_data.csv
├── notebooks/
│   └── exploratory_data_analysis.ipynb
│   └── model_training.ipynb
├── src/
│   ├── __init__.py
│   ├── data_preprocessing.py
│   ├── model_training.py
│   ├── model_evaluation.py
│   └── utilities.py
├── tests/
│   └── test_data_preprocessing.py
│   └── test_model_training.py
│   └── test_model_evaluation.py
├── .gitignore
├── .replit
├── README.md
├── main.py
├── poetry.lock
├── pyproject.toml
└── requirements.txt

Getting Started

To get started with this project, follow these steps:

1. Clone the repository:

   git clone https://github.com/canstralian/CyberAttackDetection-Python.git

2. Install the dependencies:

   pip install -r requirements.txt

Usage

Data Preprocessing

Run the data preprocessing script:

python src/data_preprocessing.py

Model Training

Train the models:

python src/model_training.py

Model Evaluation

Evaluate the models:

python src/model_evaluation.py

Contributing

Contributions are welcome! Please read the contributing guidelines for more information.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

• PyTorch
• scikit-learn