activity
20162023
most citedTAD: Transfer Learning-based Multi-Adversarial Detection of Evasion Attacks against Network Intrusion Detection Systems

77 citations · 176 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CR2023★ 4 cited

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…

cs.CR2023★ 67 cited

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…

cs.CR2022★ 77 cited

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…

cs.CR2021★ 16 cited

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…

cs.CR2021★ 7 cited

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…

cs.DS2016★ 5 cited

Fast Online k-nn Graph Building

Thibault Debatty, Pietro Michiardi, Wim Mees

In this paper we propose an online approximate k-nn graph building algorithm, which is able to quickly update a k-nn graph using a flow of data points. One very important step of t…