TARO builds a temporally guided score prior from high-noise and low-noise diffusion views to purify adversarial examples more robustly than uniform timestep methods.
Guided diffusion model for adversarial purification.arXiv preprint arXiv:2205.14969
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SAWR applies stain-aware multi-level wavelet regularization to purify adversarial perturbations in histopathology images, claiming up to 10.69% robustness gain while preserving texture and spectral properties.
A structured literature survey categorizing generative AI (autoencoders, GANs, diffusion models, LLMs) and federated learning uses in IDS, covering tasks like synthetic data generation and anomaly detection plus open challenges.
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TARO: Temporal Adversarial Rectification Optimization Using Diffusion Models as Purifiers
TARO builds a temporally guided score prior from high-noise and low-noise diffusion views to purify adversarial examples more robustly than uniform timestep methods.
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Stain-Aware Wavelet Regularization for Instant Adversarial Purification in Histopathology
SAWR applies stain-aware multi-level wavelet regularization to purify adversarial perturbations in histopathology images, claiming up to 10.69% robustness gain while preserving texture and spectral properties.
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