Evaluation of Adversarial Training on Different Types of Neural Networks in Deep Learning-based IDSs

8 July 2020

Papers citing "Evaluation of Adversarial Training on Different Types of Neural Networks in Deep Learning-based IDSs"

8 / 8 papers shown

Title
Adversarial Evasion Attacks Practicality in Networks: Testing the Impact of Dynamic Learning Mohamed el Shehaby Ashraf Matrawy AAML 33 7 0 08 Jun 2023
Improving Robustness Against Adversarial Attacks with Deeply Quantized Neural Networks Ferheen Ayaz Idris Zakariyya José Cano S. Keoh Jeremy Singer D. Pau Mounia Kharbouche-Harrari 19 5 0 25 Apr 2023
TAD: Transfer Learning-based Multi-Adversarial Detection of Evasion Attacks against Network Intrusion Detection Systems Islam Debicha Richard Bauwens Thibault Debatty Jean-Michel Dricot Tayeb Kenaza Wim Mees AAML 24 40 0 27 Oct 2022
The Cross-evaluation of Machine Learning-based Network Intrusion Detection Systems Giovanni Apruzzese Luca Pajola Mauro Conti 32 53 0 09 Mar 2022
GADoT: GAN-based Adversarial Training for Robust DDoS Attack Detection Maged AbdelAty Sandra Scott-Hayward Roberto Doriguzzi-Corin Domenico Siracusa AAML 34 23 0 31 Jan 2022
EVAGAN: Evasion Generative Adversarial Network for Low Data Regimes Rizwan Hamid Randhawa N. Aslam Mohammad Alauthman Husnain Rafiq AAML GAN 33 11 0 14 Sep 2021
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 37 68 0 06 Nov 2019
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 308 5,842 0 08 Jul 2016