5 papers · 1 filter
RobQFL: Robust Quantum Federated Learning in Adversarial Environment
Walid El Maouaki, Nouhaila Innan, Alberto Marchisio +3
Quantum Federated Learning (QFL) merges privacy-preserving federation with quantum computing gains, yet its resilience to adversarial noise is unknown. We first show that QFL is as…
Designing Robust Quantum Neural Networks via Optimized Circuit Metrics
Walid El Maouaki, Alberto Marchisio, Taoufik Said +2
In this study, we investigated the robustness of Quanvolutional Neural Networks (QuNNs) in comparison to their classical counterparts, Convolutional Neural Networks (CNNs), against…
Quantum Clustering for Cybersecurity
Walid El Maouaki, Nouhaila Innan, Alberto Marchisio +3
In this study, we develop a novel quantum machine learning (QML) framework to analyze cybersecurity vulnerabilities using data from the 2022 CISA Known Exploited Vulnerabilities ca…
RobQuNNs: A Methodology for Robust Quanvolutional Neural Networks against Adversarial Attacks
Walid El Maouaki, Alberto Marchisio, Taoufik Said +2
Recent advancements in quantum computing have led to the emergence of hybrid quantum neural networks, such as Quanvolutional Neural Networks (QuNNs), which integrate quantum and cl…
AdvQuNN: A Methodology for Analyzing the Adversarial Robustness of Quanvolutional Neural Networks
Walid El Maouaki, Alberto Marchisio, Taoufik Said +2
Recent advancements in quantum computing have led to the development of hybrid quantum neural networks (HQNNs) that employ a mixed set of quantum layers and classical layers, such…