5 papers
Empowering AI-Native 6G Wireless Networks with Quantum Federated Learning
Shaba Shaon, Md Raihan Uddin, Dinh C. Nguyen +3
AI-native 6G networks are envisioned to tightly embed artificial intelligence (AI) into the wireless ecosystem, enabling real-time, personalized, and privacy-preserving intelligenc…
Quantum Federated Learning: A Comprehensive Survey
Dinh C. Nguyen, Md Raihan Uddin, Shaba Shaon +3
Quantum federated learning (QFL) is a combination of distributed quantum computing and federated machine learning, integrating the strengths of both to enable privacy-preserving de…
SimQFL: A Quantum Federated Learning Simulator with Real-Time Visualization
Ratun Rahman, Atit Pokharel, Md Raihan Uddin +1
Quantum federated learning (QFL) is an emerging field that has the potential to revolutionize computation by taking advantage of quantum physics concepts in a distributed machine l…
False Data Injection Attack Detection in Edge-based Smart Metering Networks with Federated Learning
Md Raihan Uddin, Ratun Rahman, Dinh C. Nguyen
Smart metering networks are increasingly susceptible to cyber threats, where false data injection (FDI) appears as a critical attack. Data-driven-based machine learning (ML) method…
From Federated Learning to Quantum Federated Learning for Space-Air-Ground Integrated Networks
Vu Khanh Quy, Nguyen Minh Quy, Tran Thi Hoai +6
6G wireless networks are expected to provide seamless and data-based connections that cover space-air-ground and underwater networks. As a core partition of future 6G networks, Spa…