77 citations · 171 across the 6 of their papers we have counts for
5 papers · 1 filter
Review on the Feasibility of Adversarial Evasion Attacks and Defenses for Network Intrusion Detection Systems
Islam Debicha, Benjamin Cochez, Tayeb Kenaza +3
Nowadays, numerous applications incorporate machine learning (ML) algorithms due to their prominent achievements. However, many studies in the field of computer vision have shown t…
Adv-Bot: Realistic Adversarial Botnet Attacks against Network Intrusion Detection Systems
Islam Debicha, Benjamin Cochez, Tayeb Kenaza +3
Due to the numerous advantages of machine learning (ML) algorithms, many applications now incorporate them. However, many studies in the field of image classification have shown th…
TAD: Transfer Learning-based Multi-Adversarial Detection of Evasion Attacks against Network Intrusion Detection Systems
Islam Debicha, Richard Bauwens, Thibault Debatty +3
Nowadays, intrusion detection systems based on deep learning deliver state-of-the-art performance. However, recent research has shown that specially crafted perturbations, called a…
Detect & Reject for Transferability of Black-box Adversarial Attacks Against Network Intrusion Detection Systems
Islam Debicha, Thibault Debatty, Jean-Michel Dricot +2
In the last decade, the use of Machine Learning techniques in anomaly-based intrusion detection systems has seen much success. However, recent studies have shown that Machine learn…
Adversarial Training for Deep Learning-based Intrusion Detection Systems
Islam Debicha, Thibault Debatty, Jean-Michel Dricot +1
Nowadays, Deep Neural Networks (DNNs) report state-of-the-art results in many machine learning areas, including intrusion detection. Nevertheless, recent studies in computer vision…