9 citations · 24 across the 13 of their papers we have counts for
13 papers
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…
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…
Robust Zero Trust Architecture: Joint Blockchain based Federated learning and Anomaly Detection based Framework
Shiva Raj Pokhrel, Luxing Yang, Sutharshan Rajasegarar +1
This paper introduces a robust zero-trust architecture (ZTA) tailored for the decentralized system that empowers efficient remote work and collaboration within IoT networks. Using…
Quantum Federated Learning Experiments in the Cloud with Data Encoding
Shiva Raj Pokhrel, Naman Yash, Jonathan Kua +2
Quantum Federated Learning (QFL) is an emerging concept that aims to unfold federated learning (FL) over quantum networks, enabling collaborative quantum model training along with…
Performance Analysis and Evaluation of Post Quantum Secure Blockchained Federated Learning
Dev Gurung, Shiva Raj Pokhrel, Gang Li
Post-quantum security is critical in the quantum era. Quantum computers, along with quantum algorithms, make the standard cryptography based on RSA or ECDSA over FL or Blockchain v…
Improving Federated Aggregation with Deep Unfolding Networks
Shanika I Nanayakkara, Shiva Raj Pokhrel, Gang Li
The performance of Federated learning (FL) is negatively affected by device differences and statistical characteristics between participating clients. To address this issue, we int…
Quantum Federated Learning: Analysis, Design and Implementation Challenges
Dev Gurung, Shiva Raj Pokhrel, Gang Li
Quantum Federated Learning (QFL) has gained significant attention due to quantum computing and machine learning advancements. As the demand for QFL continues to surge, there is a p…
Decentralized Quantum Federated Learning for Metaverse: Analysis, Design and Implementation
Dev Gurung, Shiva Raj Pokhrel, Gang Li
With the emerging developments of the Metaverse, a virtual world where people can interact, socialize, play, and conduct their business, it has become critical to ensure that the u…
Secure Communication Model For Quantum Federated Learning: A Post Quantum Cryptography (PQC) Framework
Dev Gurung, Shiva Raj Pokhrel, Gang Li
We design a model of Post Quantum Cryptography (PQC) Quantum Federated Learning (QFL). We develop a framework with a dynamic server selection and study convergence and security con…
Post Quantum Secure Blockchain-based Federated Learning for Mobile Edge Computing
Rongxin Xu, Shiva Raj Pokhrel, Qiujun Lan +1
Mobile Edge Computing (MEC) has been a promising paradigm for communicating and edge processing of data on the move. We aim to employ Federated Learning (FL) and prominent features…
Digital Privacy Under Attack: Challenges and Enablers
Baobao Song, Shiva Raj Pokhrel, Mengyue Deng +3
We present a comprehensive analysis of privacy attacks and countermeasures in data-driven systems. We systematically categorize attacks targeting three domains: anonymous data (lin…
A Survey of Distributed Ledger Technology for IoT Verticals
Rongxin Xu, Qiujun Lan, Shiva Raj Pokhrel +1
The Internet of Things (IoT) and Distributed ledger technology (DLT) have significantly changed our daily lives. Due to their distributed operational environment and naturally dece…
FAIR-BFL: Flexible and Incentive Redesign for Blockchain-based Federated Learning
Rongxin Xu, Shiva Raj Pokhrel, Qiujun Lan +1
Vanilla Federated learning (FL) relies on the centralized global aggregation mechanism and assumes that all clients are honest. This makes it a challenge for FL to alleviate the si…