77 citations · 174 across the 10 of their papers we have counts for
10 papers
Robustness Evaluation of Hybrid Quantum Neural Networks under Noise Models via System-Level Error Mitigation
Jesse Roberta Mingue Njiki, Nouhaila Innan, Alberto Marchisio +3
Quantum Neural Networks (QNNs) represent a promising direction within Quantum Machine Learning (QML), yet their realization on noisy intermediate-scale quantum (NISQ) devices remai…
Targeted Adversarial Traffic Generation : Black-box Approach to Evade Intrusion Detection Systems in IoT Networks
Islam Debicha, Tayeb Kenaza, Ishak Charfi +3
The integration of machine learning (ML) algorithms into Internet of Things (IoT) applications has introduced significant advantages alongside vulnerabilities to adversarial attack…
Systematic Assessment of Cache Timing Vulnerabilities on RISC-V Processors
Cédrick Austa, Jan Tobias Mühlberg, Jean-Michel Dricot
While interest in the open RISC-V instruction set architecture is growing, tools to assess the security of concrete processor implementations are lacking. There are dedicated tools…
Towards an Efficient Simulation Approach for Transmission Systems with ICT Infrastructures
Frédéric Sabot, Pierre-Etienne Labeau, Jean-Michel Dricot +1
With the transition towards a smart grid, Information and Communications Technology (ICT) infrastructures play a growing role in the operation of transmission systems. Cyber-physic…
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…
CSI-based versus RSS-based Secret-Key Generation under Correlated Eavesdropping
François Rottenberg, Trung-Hien Nguyen, Jean-Michel Dricot +2
Physical-layer security (PLS) has the potential to strongly enhance the overall system security as an alternative to or in combination with conventional cryptographic primitives us…