5 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…
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…
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…