我们评估对三个标准数据集的攻击:MNIST ,一个数字识别任务(0-9); CIFAR-10 ,一个小图像识别任务,也有10个类别; 和ImageNet ,这是一个具有1000个类别的大图像识别任务。 图1显示了我们的技术在经过MNIST和CIFAR数据集训练的防御性蒸馏网络上生成的对抗性示例。 在ImageNet分类任务的一个极端示例中,我们可以通过...
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach 简介: 本文主要提出了一种 不依赖于特定攻击 (attack-agnostic) 的衡量模型鲁棒性的一种方法。作者称之为 CLEVER (Cross Lipschitz Extreme Value for nEtwork Robustness). 该方法特点如下: attack-agnostic 计算量合理,可应用于大型深...
【论文回顾】Towards Evaluating the Robustness of Neural Networks,程序员大本营,技术文章内容聚合第一站。
[论文笔记] Towards Evaluating the Robustness of Neural Networks 说在前面 个人心得: 文章有点冗长,实验很多,但是读来感觉不是很清晰 提出的攻击方法主要是基于优化 我觉得简单的数据集迁移性会比较明显,迁移性这个实验还是不够有说服力 2017 IEEE Symposium on Security and Privacy,原文链接:http://arxiv.org/...
Nicholas Carlini, David Wagner, Towards Evaluating the Robustness of Neural Networks概提出了在不同范数下ℓ0,ℓ2,ℓ∞ℓ0,ℓ2,ℓ∞下生成adversarial samples的方法, 实验证明此类方法很有效.主要内容基本的概念本文主要针对多分类问题, 假设神经网络...
In this paper, we demonstrate that defensive distillation does not significantly increase the robustness of neural networks by introducing three new attack algorithms that are successful on both distilled and undistilled neural networks with 100% probability. Our attacks are tailored to three distance ...
Network robustness has been a hot research area of studies on complex networks. Finding out the explanations behind the phenomena that networked systems can still function efficiently after some structural damages or the malfunction of certain nodes is meaningful to both the design of solid systems ...
RVCL: Evaluating the Robustness of Contrastive Learning via Verification (JMLR 2023) 刘威威实验室 欢迎数学/统计、计算机相关专业学生报考我组硕、博、博后。4 人赞同了该文章 作者:Zekai Wang, Weiwei Liu 文章介绍了一种新颖的对比学习鲁棒验证框架(RVCL),解决了现有对比对抗训练方法的局限性。RVCL从确定性和...
The interest in diversity as a security mechanism has recently been revived in various applications, such as Moving Target Defense (MTD), resisting worms in sensor networks, and improving the robustness of network routing. However, most existing efforts on formally modeling diversity have focused on...
Evaluating the robustness of models developed from field spectral data in predicting African grass foliar nitrogen concentration using WorldView-2 image as an independent test dataset. International Journal of Applied Earth Observation and Geoinformation, 34, pp.178-187....