Anomaly-based network intrusion detection using denoising autoencoder and Wasserstein GAN synthetic attacks.
Saved in:
| Title: | Anomaly-based network intrusion detection using denoising autoencoder and Wasserstein GAN synthetic attacks. |
|---|---|
| Authors: | Arafah, Mohammad1, Mohammad.Arafah@uop.edu.jo, Phillips, Iain2, i.w.phillips@lboro.ac.uk, Adnane, Asma2, a.adnane@lboro.ac.uk, Hadi, Wael1, whadi@uop.edu.jo, Alauthman, Mohammad1, mohammad.alauthman@uop.edu.jo, Al-Banna, Abedal-Kareem3, abanna@uop.edu.jo |
| Source: | Applied Soft Computing; Jan2025, Vol. 168, pN.PAG-N.PAG, 1p |
| Database: | Applied Science & Technology Source |
| ISSN: | 15684946 |
|---|---|
| DOI: | 10.1016/j.asoc.2024.112455 |
