A New Defense Against Adversarial Images: Turning a Weakness into a Strength

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A New Defense Against Adversarial Images: Turning a Weakness into a Strength

目录概主要内容准则1 准则2 总策略 Hu S, Yu T, Guo C, et al. A New Defense Against Adversarial Images: Turning a Weakness into a Strength[C]. neural information processing systems, 2019: 1633-1644. @article{hu2019a, title={A New Defense Against Adversarial Images…

Limitations of the Lipschitz constant as a defense against adversarial examples

目录概主要内容 Huster T., Chiang C. J. and Chadha R. Limitations of the lipschitz constant as a defense against adversarial examples. In European Conference on Machine Learning and Data Mining (ECML PKDD), 2018. 概本文是想说明现有的依赖Lipschitz常数的以获得可验证的鲁棒性存在很大局限性.…

Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks

目录概主要内容算法一些有趣的指标鲁棒性定义合格的抗干扰机制 Nicolas Papernot, Patrick McDaniel, Xi Wu, Somesh Jha, Ananthram Swami, Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks. 概本文提出一种distillation model, 能够免疫大部分的adversarial attacks,…

（转）Awesome Knowledge Distillation

Awesome Knowledge Distillation 2018-07-19 10:38:40 Reference:https://github.com/dkozlov/awesome-knowledge-distillation Papers Combining labeled and unlabeled data with co-training, A. Blum, T. Mitchell, 1998 Model Compression, Rich Caruana, 2006 Dar…

（转）Is attacking machine learning easier than defending it?

转自:http://www.cleverhans.io/security/privacy/ml/2017/02/15/why-attacking-machine-learning-is-easier-than-defending-it.html Is attacking machine learning easier than defending it? Feb 15, 2017 by Ian Goodfellow and Nicolas Papernot In our first post…

Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks

目录概主要内容 Mustafa A., Khan S., Hayat M., Goecke R., Shen J., Shao L., Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, arXiv preprint arXiv:1904.00887, 2019. 代码概类似的, 是large margin的思想, 亮点是多层? 主要内容以下, \(f^l\)表示第\(l\)层的输入,…

DEFENSE-GAN: PROTECTING CLASSIFIERS AGAINST ADVERSARIAL ATTACKS USING GENERATIVE MODELS

目录概主要内容 Samangouei P, Kabkab M, Chellappa R, et al. Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models.[J]. arXiv: Computer Vision and Pattern Recognition, 2018. @article{samangouei2018defense-gan:, title={Defen…

Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

目录概主要内容 Obfuscated Gradients BPDA 特例一般情形 EOT Reparameterization 具体的案例 Thermometer encoding Input transformations LID Stochastic Activation Pruning Mitigating through randomization PixelDefend DenfenseGAN Athalye A, Carlini N, Wagner D, et al. Obfu…

Automysqlbackup: WARNING: Turning off multicore support, since pigz isn’t there.

在使用Automysqlbackup备份MySQL时,有时候你会在邮件里面看见"WARNING: Turning off multicore support, since pigz isn't there."这样的告警信息,为什么会出现这个告警信息呢? 错误原因: Automysqlbackup在备份MySQL数据库时会去压缩dump文件.而且支持多处理器.它默认使用pigz进行压缩处理.也就是说默认是开启Multicore Support.pigz 是一个 gzip 的并行实现版本,…

StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks 论文笔记

StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks 本文将利用 GANs 进行高质量图像生成,分为两个阶段进行,coarse to fine 的过程.据说可以生成 256*256 的高清图像. 基于文本生成对应图像的工作已经有了,比如说 Attribute2Image,以及最开始的基于文本生成图像的文章等等. Stacked Generated Adver…