Adversarial Examples(对抗样本) 对抗样本(adversarial examples)和对抗学习(GAN)截然不同,这一概念在Szegedyet al. (2014b)中提出:对输入样本故意添加一些人无法察觉的细微的干扰,导致模型以高置信度给出一个错误的输出。 1.可以针对一张已经有正确分类的image,对其进行细微的像素修改,可以在DNN下被错分为其他label。
Adversarial Objects Against LiDAR-Based Autonomous Driving Systemshttps://arxiv.org/pdf/1907.05418.pdf Audio Adversarial Examples: Targeted Attacks on Speech-to-Texthttps://arxiv.org/pdf/1801.01944.pdf Adversarial T-shirt! Evading Person Detectors in A Physical Worldhttps://arxiv.org/pdf/1910.11099....
Explaining and harnessing adversarial examples 心妍 我要解放你 标题:ADVERSARIAL EXAMPLES IN THE PHYSICAL WORLD Link:http://research.google.com/pubs/pub45471.htmlA. Problem Statement This… 阅读全文 对抗网络做图像的分类问题? 霍华德 楼主运用原始GAN做分类是什么思想呢?G网络的作用是什么?
模型融合对于对抗样本的防御能力非常有限 RBF networks are resistant to adversarial examples 知乎:https://zhuanlan.zhihu.com/p/32784766 之后又有论文证明 Adversarial examples in the physical worldAlexey Kurakin,Ian Goodfellow,Samy BengioICLR2017 workshop 证明真实数据在物理世界是存在的 未来的工作,就是希望不...
Physically Realizable Adversarial Examples for LiDAR Object Detection PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving ILFO: Adversarial Attack on Adaptive Neural Networks Noise Is Inside Me! Generating Adversarial Perturbations With Noise Derived From Natural Filters Learn...
Adversarial examples in the physical world(CVPR 2016):提出BIM方法,即优化时用若干小步代替一大步,进一步提出non-targeted版本,Iterative Least-likely Class Method (ILCM). 作者单位: Google. Jacobian-based Saliency Map Attack (JSMA): The Limitations of Deep Learning in Adversarial Settings(EURO S&P): ...
Enhance the Visual Representation via Discrete Adversarial Training Isometric 3D Adversarial Examples in the Physical World CalFAT: Calibrated Federated Adversarial Training with Label Skewness On the Limitations of Stochastic Pre-processing Defenses
3) BASIC & LEAST-LIKELY-CLASS ITERATIVE METHODS [1607.02533] Adversarial examples in the physical world (arxiv.org) one-step 的方法通过向着增大分类器损失的方向迈一步来产生干扰,以此来干扰图片。 这个想法的一个直观扩展就是迭代地采取多个小步骤,同时在每个步骤之后调整方向。The Basic Iterative Method(...
对于对抗样本(adversarial examples)的相关工作而言,Goodfellow等人提出的这篇Explaining and Harnessing Adversarial Examples论文可以说是经典中的经典了。 在这篇论文中,Goodfellow等人对现有的工作进行了一个全面的总结,更重要的是,这篇论文: 解释了神经网络对干扰表现脆弱的原因是神经网络的线性(而早期的解释是对抗样本...
与Adversarial T-shirt非常类似,开篇表述没有特殊的内容,不过有句话可以作为对physical attack攻击特点的概括: However, in most realistic situations the attackers has only black or grey knowledge, their attack must transfer from the digital world into the physical world, from the attacker model to the ...