Guardians of the Quantum GAN

arXiv:2404.16156v1 Announce Type: cross
Abstract: Quantum Generative Adversarial Networks (qGANs) are at the forefront of image-generating quantum machine learning models. To accommodate the growing demand for Noisy Intermediate-Scale Quantum (NISQ) devices to train and infer quantum machine learning models, the number of third-party vendors offering quantum hardware as a service is expected to rise. This expansion introduces the risk of untrusted vendors potentially stealing proprietary information from the quantum machine learning models. To address this concern we propose a novel …

adversarial arxiv cs.ar cs.cr cs.lg demand devices gan generative generative adversarial networks guardians hardware image intermediate machine machine learning machine learning models networks noisy party quant-ph quantum scale service third third-party third-party vendors train vendors