QuantumLeak: Stealing Quantum Neural Networks from Cloud-based NISQ Machines

arXiv:2403.10790v1 Announce Type: cross
Abstract: 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 serve as valuable intellectual assets hosted on cloud-based Noisy Intermediate Scale Quantum (NISQ) computers, making them susceptible to malicious VQC stealing attacks. However, traditional model extraction techniques designed for classical machine learning models encounter challenges when applied to NISQ computers due to significant noise in current devices. In this paper, we …

arxiv assets attacks cloud cloud-based computers cs.cr cs.lg intermediate machines making malicious networks neural networks noisy problems quant-ph quantum scale stealing tool