The QC-GAN uses a quantum generator to produce adversarial network flows that evade classical IDS models such as random forest and CNN on the UNSW-NB15 dataset.
Variational quantum circuits enhanced generative adversarial network
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Fully hybrid quantum-classical GANs with VQCs in both generator and discriminator outperform classical baselines in image quality and metrics, with placement effects on convergence and sustained performance on reduced datasets.
citing papers explorer
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Hybrid Quantum-Classical GANs for the Generation of Adversarial Network Flows
The QC-GAN uses a quantum generator to produce adversarial network flows that evade classical IDS models such as random forest and CNN on the UNSW-NB15 dataset.
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Hybrid Quantum-Classical Generative Adversarial Networks with Transfer Learning
Fully hybrid quantum-classical GANs with VQCs in both generator and discriminator outperform classical baselines in image quality and metrics, with placement effects on convergence and sustained performance on reduced datasets.