4 citations · 4 across the 8 of their papers we have counts for
4 papers · 1 filter
CopyQNN: Quantum Neural Network Extraction Attack under Varying Quantum Noise
Zhenxiao Fu, Leyi Zhao, Xuhong Zhang +3
Quantum Neural Networks (QNNs) have shown significant value across domains, with well-trained QNNs representing critical intellectual property often deployed via cloud-based QNN-as…
Quantum Neural Network Extraction Attack via Split Co-Teaching
Zhenxiao Fu, Fan Chen
Quantum Neural Networks (QNNs), now offered as QNN-as-a-Service (QNNaaS), have become key targets for model extraction attacks. Existing methods use ensemble learning to train subs…
QuantumLeak: Stealing Quantum Neural Networks from Cloud-based NISQ Machines
Zhenxiao Fu, Min Yang, Cheng Chu +3
Variational quantum circuits (VQCs) have become a powerful tool for implementing Quantum Neural Networks (QNNs), addressing a wide range of complex problems. Well-trained VQCs serv…
TITAN: A Distributed Large-Scale Trapped-Ion NISQ Computer
Cheng Chu, Zhenxiao Fu, Yilun Xu +4
Trapped-Ion (TI) technology offers potential breakthroughs for Noisy Intermediate Scale Quantum (NISQ) computing. TI qubits offer extended coherence times and high gate fidelity, m…