57 citations · 95 across the 51 of their papers we have counts for
22 papers · 1 filter
Black-Box Auditing of Quantum Model: Lifted Differential Privacy with Quantum Canaries
Baobao Song, Shiva Raj Pokhrel, Athanasios V. Vasilakos +2
Quantum machine learning (QML) promises significant computational advantages, yet models trained on sensitive data risk memorizing individual records, creating serious privacy vuln…
Scaling Trust in Quantum Federated Learning: A Multi-Protocol Privacy Design
Dev Gurung, Shiva Raj Pokhrel
Quantum Federated Learning (QFL) promises to revolutionize distributed machine learning by combining the computational power of quantum devices with collaborative model training. Y…
Quantum Vanguard: Server Optimized Privacy Fortified Federated Intelligence for Future Vehicles
Dev Gurung, Shiva Raj Pokhrel
This work presents vQFL (vehicular Quantum Federated Learning), a new framework that leverages quantum machine learning techniques to tackle key privacy and security issues in auto…
TCP BBR Performance over Wi-Fi~6: AQM Impacts and Cross-Layer Insights
Shyam Kumar Shrestha, Shiva Raj Pokhrel, Jonathan Kua
We evaluate TCP BBRv3 on Wi-Fi 6 home networks under modern AQM schemes using a fully wireless testbed and a simple cross-layer model linking Wi-Fi scheduling, router queueing, and…
Adaptive Aggregation with Two Gains in QFL
S Nanayakkara
Federated learning (FL) deployed over quantum enabled and heterogeneous classical networks faces significant performance degradation due to uneven client quality, stochastic telepo…
Modeling Wavelet Transformed Quantum Support Vector for Network Intrusion Detection
Swati Kumari, Shiva Raj Pokhrel, Swathi Chandrasekhar +5
Network traffic anomaly detection is a critical cybersecurity challenge requiring robust solutions for complex Internet of Things (IoT) environments. We present a novel hybrid quan…
Modeling Quantum Autoencoder Trainable Kernel for IoT Anomaly Detection
Swathi Chandrasekhar, Shiva Raj Pokhrel, Swati Kumari +1
Escalating cyber threats and the high-dimensional complexity of IoT traffic have outpaced classical anomaly detection methods. While deep learning offers improvements, computationa…
Lane-Frame Quantum Multimodal Driving Forecasts for the Trajectory of Autonomous Vehicles
Navneet Singh, Shiva Raj Pokhrel
Trajectory forecasting for autonomous driving must deliver accurate, calibrated multi-modal futures under tight compute and latency constraints. We propose a compact hybrid quantum…
QuantumShield: Multilayer Fortification for Quantum Federated Learning
Dev Gurung, Shiva Raj Pokhrel
In this paper, we propose a groundbreaking quantum-secure federated learning (QFL) framework designed to safeguard distributed learning systems against the emerging threat of quant…
Adapting Quantum Machine Learning for Energy Dissociation of Bonds
Swathi Chandrasekhar, Shiva Raj Pokhrel, Navneet Singh
Accurate prediction of bond dissociation energies (BDEs) underpins mechanistic insight and the rational design of molecules and materials. We present a systematic, reproducible ben…
orb-QFL: Orbital Quantum Federated Learning
Dev Gurung, Shiva Raj Pokhrel
Recent breakthroughs in quantum computing present transformative opportunities for advancing Federated Learning (FL), particularly in non-terrestrial environments characterized by…
sat-QFL: Secure Quantum Federated Learning for Low Orbit Satellites
Dev Gurung, Shiva Raj Pokhrel
Low Earth orbit (LEO) constellations violate core assumptions of standard (quantum) federated learning (FL): client-server connectivity is intermittent, participation is time varyi…
Understanding BBRv3 Performance in AQM-Enabled WiFi Networks
Shyam Kumar Shrestha, Jonathan Kua, Shiva Raj Pokhrel
We present a modular experimental testbed and lightweight visualization tool for evaluating TCP congestion control performance in wireless networks. We compare Google's latest Bott…
Towards Adapting Federated & Quantum Machine Learning for Network Intrusion Detection: A Survey
Devashish Chaudhary, Sutharshan Rajasegarar, Shiva Raj Pokhrel
This survey explores the integration of Federated Learning (FL) with Network Intrusion Detection Systems (NIDS), with particular emphasis on deep learning and quantum machine learn…
Intelligent Spectrum Management in Satellite Communications
Rakshitha De Silva, Shiva Raj Pokhrel, Jonathan Kua +1
Satellite Communication (SatCom) networks represent a fundamental pillar in modern global connectivity, facilitating reliable service and extensive coverage across a plethora of ap…
New Insights on Unfolding and Fine-tuning Quantum Federated Learning
Shanika Iroshi Nanayakkara, Shiva Raj Pokhrel
Client heterogeneity poses significant challenges to the performance of Quantum Federated Learning (QFL). To overcome these limitations, we propose a new approach leveraging deep u…
Communication Efficient Adaptive Model-Driven Quantum Federated Learning
Dev Gurung, Shiva Raj Pokhrel
Training with huge datasets and a large number of participating devices leads to bottlenecks in federated learning (FL). Furthermore, the challenges of heterogeneity between multip…
LLM-QFL: Distilling Large Language Model for Quantum Federated Learning
Dev Gurung, Shiva Raj Pokhrel
Inspired by the power of large language models (LLMs), our research adapts them to quantum federated learning (QFL) to boost efficiency and performance. We propose a federated fine…
Towards A Hybrid Quantum Differential Privacy
Baobao Song, Shiva Raj Pokhrel, Athanasios V. Vasilakos +2
Quantum computing offers unparalleled processing power but raises significant data privacy challenges. Quantum Differential Privacy (QDP) leverages inherent quantum noise to safegu…
Modeling Feature Maps for Quantum Machine Learning
Navneet Singh, Shiva Raj Pokhrel
Quantum Machine Learning (QML) offers significant potential for complex tasks like genome sequence classification, but quantum noise on Noisy Intermediate-Scale Quantum (NISQ) devi…
Modeling Quantum Machine Learning for Genomic Data Analysis
Navneet Singh, Shiva Raj Pokhrel
Quantum Machine Learning (QML) continues to evolve, unlocking new opportunities for diverse applications. In this study, we investigate and evaluate the applicability of QML models…
Distilling Large Language Models for Network Active Queue Management
Shiva Raj Pokhrel, Deol Satish, Jonathan Kua +1
The growing complexity of network traffic and demand for ultra-low latency communication require smarter packet traffic management. Existing Deep Learning-based queuing approaches…