/adversarial_ml_ids

Adversarial Machine Learning applications on network-based Intrusion Detection System (IDS).

Primary LanguagePythonMIT LicenseMIT

Adversarial Examples on the IDS Dataset

The repo is created to maintain the code base of the Adversarial Machine Learning applications, such as, Model Evasion Attack, on the publically accessible dataset of network-based Intrusion Detection System (IDS).

The work has been published at the IEEE 2020 54th Annual Conference on Information Sciences and Systems (CISS).

Citing this work

If you use our implementation for academic research, you are highly encouraged to cite our paper.

@inproceedings{ayub2020model,
  author={M. A. {Ayub} and W. A. {Johnson} and D. A. {Talbert} and A. {Siraj}},
  booktitle={2020 54th Annual Conference on Information Sciences and Systems (CISS)}, 
  title={Model Evasion Attack on Intrusion Detection Systems using Adversarial Machine Learning}, 
  year={2020}
  pages={1-6}
}

The work has been funded by Cybersecurity Education, Research & Outreach Center (CEROC) at Tennessee Tech University.