112 citations · 455 across the 21 of their papers we have counts for
21 papers
Q-SYNTH: Hybrid Quantum-Classical Adversarial Augmentation for Imbalanced Fraud Detection
Adam Innan, Mansour El Alami, Nouhaila Innan +2
Credit card fraud detection is fundamentally challenged by extreme class imbalance, where fraudulent transactions are rare yet operationally critical. This imbalance often biases s…
FiD-QAE: A Fidelity-Driven Quantum Autoencoder for Credit Card Fraud Detection
Mansour El Alami, Adam Innan, Nouhaila Innan +2
Credit card fraud detection is a critical task in financial security, as fraudulent transactions are rare, highly imbalanced, and often resemble legitimate ones. A wide range of cl…
Benchmarking VQE Configurations: Architectures, Initializations, and Optimizers for Silicon Ground State Energy
Zakaria Boutakka, Nouhaila Innan, Muhammed Shafique +2
Quantum computing presents a promising path toward precise quantum chemical simulations, particularly for systems that challenge classical methods. This work investigates the perfo…
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…
Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy
Nouhaila Innan, Muhammad Kashif, Alberto Marchisio +2
This paper provides an integrated perspective on addressing key challenges in developing reliable and secure Quantum Neural Networks (QNNs) in the Noisy Intermediate-Scale Quantum…
QFAL: Quantum Federated Adversarial Learning
Walid El Maouaki, Nouhaila Innan, Alberto Marchisio +3
Quantum federated learning (QFL) merges the privacy advantages of federated systems with the computational potential of quantum neural networks (QNNs), yet its vulnerability to adv…
Quantum Bayesian Networks for Machine Learning in Oil-Spill Detection
Owais Ishtiaq Siddiqui, Nouhaila Innan, Alberto Marchisio +2
Quantum Machine Learning (QML) has shown promise in diverse applications such as environmental monitoring, healthcare diagnostics, and financial modeling. However, its practical im…
Comparative Performance Analysis of Quantum Machine Learning Architectures for Credit Card Fraud Detection
Mansour El Alami, Nouhaila Innan, Muhammad Shafique +1
As financial fraud becomes increasingly complex, effective detection methods are essential. Quantum Machine Learning (QML) introduces certain capabilities that may enhance both acc…
LEP-QNN: Loan Eligibility Prediction using Quantum Neural Networks
Nouhaila Innan, Alberto Marchisio, Mohamed Bennai +1
Predicting loan eligibility with high accuracy remains a significant challenge in the finance sector. Accurate predictions enable financial institutions to make informed decisions,…
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…
QFNN-FFD: Quantum Federated Neural Network for Financial Fraud Detection
Nouhaila Innan, Alberto Marchisio, Mohamed Bennai +1
This study introduces the Quantum Federated Neural Network for Financial Fraud Detection (QFNN-FFD), a cutting-edge framework merging Quantum Machine Learning (QML) and quantum com…
FedQNN: Federated Learning using Quantum Neural Networks
Nouhaila Innan, Muhammad Al-Zafar Khan, Alberto Marchisio +2
In this study, we explore the innovative domain of Quantum Federated Learning (QFL) as a framework for training Quantum Machine Learning (QML) models via distributed networks. Conv…
Brain Tumor Diagnosis Using Quantum Convolutional Neural Networks
Muhammad Al-Zafar Khan, Abdullah Al Omar Galib, Nouhaila Innan +1
Accurate classification of brain tumors from MRI scans is critical for effective treatment planning. This study presents a Hybrid Quantum Convolutional Neural Network (HQCNN) that…
Financial Fraud Detection using Quantum Graph Neural Networks
Nouhaila Innan, Abhishek Sawaika, Ashim Dhor +7
Financial fraud detection is essential for preventing significant financial losses and maintaining the reputation of financial institutions. However, conventional methods of detect…
Quantum State Tomography using Quantum Machine Learning
Nouhaila Innan, Owais Ishtiaq Siddiqui, Shivang Arora +6
Quantum State Tomography (QST) is a fundamental technique in Quantum Information Processing (QIP) for reconstructing unknown quantum states. However, the conventional QST methods a…
Financial Fraud Detection: A Comparative Study of Quantum Machine Learning Models
Nouhaila Innan, Muhammad Al-Zafar Khan, Mohamed Bennai
In this research, a comparative study of four Quantum Machine Learning (QML) models was conducted for fraud detection in finance. We proved that the Quantum Support Vector Classifi…
Simulation of a Variational Quantum Perceptron using Grover's Algorithm
Nouhaila Innan, Mohamed Bennai
The quantum perceptron, the variational circuit, and the Grover algorithm have been proposed as promising components for quantum machine learning. This paper presents a new quantum…
Electronic Structure Calculations using Quantum Computing
Nouhaila Innan, Muhammad Al-Zafar Khan, Mohamed Bennai
The computation of electronic structure properties at the quantum level is a crucial aspect of modern physics research. However, conventional methods can be computationally demandi…
Enhancing Quantum Support Vector Machines through Variational Kernel Training
Nouhaila Innan, Muhammad Al-Zafar Khan, Biswaranjan Panda +1
Quantum machine learning (QML) has witnessed immense progress recently, with quantum support vector machines (QSVMs) emerging as a promising model. This paper focuses on the two ex…