251 citations · 833 across the 65 of their papers we have counts for
8 papers · 1 filter
Quantum Gated Recurrent GAN with Gaussian Uncertainty for Network Anomaly Detection
Wajdi Hammami, Soumaya Cherkaoui, Jean-Frederic Laprade +2
Anomaly detection in time-series data is a critical challenge with significant implications for network security. Recent quantum machine learning approaches, such as quantum kernel…
Multivariate Time Series Forecasting with Gate-Based Quantum Reservoir Computing on NISQ Hardware
Wissal Hamhoum, Soumaya Cherkaoui, Jean-Frederic Laprade +2
Quantum reservoir computing (QRC) offers a hardware-friendly approach to temporal learning, yet most studies target univariate signals and overlook near-term hardware constraints.…
Federated Learning-based MARL for Strengthening Physical-Layer Security in B5G Networks
Deemah H. Tashman, Soumaya Cherkaoui, Walaa Hamouda
This paper explores the application of a federated learning-based multi-agent reinforcement learning (MARL) strategy to enhance physical-layer security (PLS) in a multi-cellular ne…
Maximizing Reliability in Overlay Radio Networks with Time Switching and Power Splitting Energy Harvesting
Deemah H. Tashman, Soumaya Cherkaoui, Walaa Hamouda
Cognitive radio networks (CRNs) are acknowledged for their ability to tackle the issue of spectrum under-utilization. In the realm of CRNs, this paper investigates the energy effic…
Optimizing Cognitive Networks: Reinforcement Learning Meets Energy Harvesting Over Cascaded Channels
Deemah H. Tashman, Soumaya Cherkaoui, Walaa Hamouda
This paper presents a reinforcement learning (RL) based approach to improve the physical layer security (PLS) of an underlay cognitive radio network (CRN) over cascaded channels. T…
Performance Optimization of Energy-Harvesting Underlay Cognitive Radio Networks Using Reinforcement Learning
Deemah H. Tashman, Soumaya Cherkaoui, Walaa Hamouda
In this paper, a reinforcement learning technique is employed to maximize the performance of a cognitive radio network (CRN). In the presence of primary users (PUs), it is presumed…
Enhancing Network Anomaly Detection with Quantum GANs and Successive Data Injection for Multivariate Time Series
Wajdi Hammami, Soumaya Cherkaoui, Shengrui Wang
Quantum computing may offer new approaches for advancing machine learning, including in complex tasks such as anomaly detection in network traffic. In this paper, we introduce a qu…
Open RAN Slicing with Quantum Optimization
Patatchona Keyela, Soumaya Cherkaoui
RAN slicing technology is a key aspect of the Open RAN paradigm, allowing simultaneous and independent provision of various services such as ultra-reliable low-latency communicatio…