This repository contains synthetically generated DDoS (Distributed Denial of Service) datasets using three different generative models: CTGAN, TVAE, and CopulaGAN. These datasets can be used for various purposes such as testing DDoS detection algorithms, training machine learning models, and benchmarking security solutions.
DDoS attacks are a significant concern in the realm of cybersecurity, and having access to realistic and diverse datasets is crucial for developing effective defence mechanisms. This repository provides synthetic DDoS datasets generated using state-of-the-art generative models. These datasets are designed to closely mimic the characteristics of real-world DDoS traffic while ensuring data privacy and security.
The repository contains three separate datasets, each corresponding to the output of one of the generative models mentioned above. These datasets are stored in CSV format and consist of synthetic DDoS traffic features.
If you use this dataset, please cite it as follows:
S. Saka, A. Al-Ataby and V. Selis, "Generating Synthetic Tabular Data for DDoS Detection Using Generative Models," 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Exeter, United Kingdom, 2023, pp. 1436-1442, doi: 10.1109/TrustCom60117.2023.00196.
By using these synthetic DDoS datasets, we hope to facilitate the advancement of DDoS detection techniques and contribute to the overall improvement of cybersecurity solutions. If you have any questions or feedback, please don't hesitate to create an issue or contact us directly.