DNN-CTGAN

Enhancing Intrusion Detection through Deep Learning and Generative Adversarial Network

Table of Content

• Getting Started
  • Datasets
  • Prerequisites
• Download and install code
• Authors
• References

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Datasets

Tools

• Anaconda (Python v3.9.18)
• Jupyter Notebook (v7.0.8)

Prerequisites

• scikit-learn (v1.2.2)
• matplotlib (v3.7.4)
• numpy (v1.23.5)
• pandas (v2.0.3)
• keras (v2.12.0)
• tensorflow (v2.12.0)
• ydata-synthetic (v1.3.1)
• pickle (v0.7.5)
• seaborn (v0.13.2)

Download and install code

• Retrieve the code

git clone https://github.com/habib-tamuk/DNN-CTGAN.git

Authors

Md Habibur Rahman, Leo Martinez III, Avdesh Mishra, Mais Nijim, Ayush Goyal and David Hicks.

For any issue please contact Avdesh Mishra, avdesh.mishra@tamuk.edu

References

1. M. H. Rahman, L. Martinez III, A. Mishra, M. Nijim, A. Goyal and D. Hicks, "Enhancing Intrusion Detection through Deep Learning and Generative Adversarial Network" accepted in 4. Interdisciplinary Conference on Electrics and Computer (INTCEC 2024) 11-13 June 2024, Chicago-USA