2.1 Evasion attacks against diffusion-based purification 基于扩散的净化防御利用扩散模型首先用高斯噪声扩散对抗样本,然后进行采样以消除噪声。通过这种方式,由于扩散模型的训练分布是干净的,因此希望也可以消除精心设计的对抗扰动。扩散长度(即总扩散时间步长)通常很大,并且在每个时间步长,深度神经网络用于估计数据分布的梯...
As a reaction, adversarial purification has emerged as a compelling solution, particularly with diffusion models showing promising results. However, their purification potential remains unexplored in the context of intrusion detection. This paper demonstrates the effectiveness of diffusion models in purifying...
[Guided Diffusion Model for Adversarial Purification](http://arxiv.org/abs/2106.09667)比较有意思的是,两篇文章都是用diffusion来做对抗样本防御(去噪)的,论文标题就差了一个字(笑),意外碰上了,让我们来看看上交和英伟达的论文那个更remarkable !
117 (2023-11-13) Adversarial Purification for Data-Driven Power System Event Classifiers with Diffusion Models https://arxiv.org/pdf/2311.07110.pdf 118 (2023-11-12) Sampler Scheduler for Diffusion Models https://arxiv.org/pdf/2311.06845.pdf 119 (2023-11-12) IMPUS Image Morphing with Perceptu...
code/stat.py: run statistics on success rate, transferability and anti-purification power [to be released] Cited as: @article{xue2023diffusion, title={Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability}, author={Xue, Haotian and Araujo, Alexandre and Hu, Bin...
purification/adp.pyCode for adversarial purification. guided_diffusion/*Code for DDPM on ImageNet. pytorch_diffusion/*Code for DDPM on CIFAR-10. networks/*Code for used classifier network architectures. utils/*Utility files. For the configuration files, we use the pixel ranges[0, 255]for the pe...
我们的方法得到了SOTA的robustness和accuracy：我们还提出了一种purification的办法。diffpure通过加噪去噪，...
Online adversarial purification based on self-supervision. arXiv preprint arXiv:2101.09387, 2021. 7 [79] Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, et al. Make-a-video: Text...
【Diffpure-2022 ICML】针对adversarial图像的“denoise(purification)”来进行防御 Diffpure 两个任务使用diffusion的框架一致,源图像(stroke image/adversarial image)经过forward加噪,再reverse出目标图像(realistic image)。需要考虑forward step:决定faithful和realistic之间的trade off。 显式分类器(/classifier guidance)...
Adversarial purification with score-based generative models Threat Model-Agnostic Adversarial Defense using Diffusion Models Guided Diffusion Model for Adversarial Purification Guided Diffusion Model for Adversarial Purification from Random Noise PointDP: Diffusion-driven Purification against Adversarial Attacks on ...