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Adversarial Defense

55 papers with code · Adversarial

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Greatest papers with code

Technical Report on the CleverHans v2.1.0 Adversarial Examples Library

3 Oct 2016tensorflow/cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

ADVERSARIAL ATTACK ADVERSARIAL DEFENSE

The Limitations of Deep Learning in Adversarial Settings

24 Nov 2015openai/cleverhans

In this work, we formalize the space of adversaries against deep neural networks (DNNs) and introduce a novel class of algorithms to craft adversarial samples based on a precise understanding of the mapping between inputs and outputs of DNNs.

ADVERSARIAL ATTACK ADVERSARIAL DEFENSE

Adversarial Examples on Graph Data: Deep Insights into Attack and Defense

5 Mar 2019stellargraph/stellargraph

Based on this observation, we propose a defense approach which inspects the graph and recovers the potential adversarial perturbations.

ADVERSARIAL ATTACK ADVERSARIAL DEFENSE

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

ICML 2018 anishathalye/obfuscated-gradients

We identify obfuscated gradients, a kind of gradient masking, as a phenomenon that leads to a false sense of security in defenses against adversarial examples.

ADVERSARIAL ATTACK ADVERSARIAL DEFENSE

Feature Denoising for Improving Adversarial Robustness

CVPR 2019 facebookresearch/ImageNet-Adversarial-Training

This study suggests that adversarial perturbations on images lead to noise in the features constructed by these networks.

ADVERSARIAL DEFENSE ADVERSARIAL TRAINING IMAGE CLASSIFICATION

Towards Deep Learning Models Resistant to Adversarial Attacks

ICLR 2018 MadryLab/mnist_challenge

Its principled nature also enables us to identify methods for both training and attacking neural networks that are reliable and, in a certain sense, universal.

ADVERSARIAL DEFENSE

Countering Adversarial Images using Input Transformations

ICLR 2018 facebookresearch/adversarial_image_defenses

This paper investigates strategies that defend against adversarial-example attacks on image-classification systems by transforming the inputs before feeding them to the system.

ADVERSARIAL DEFENSE IMAGE CLASSIFICATION

Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

ICLR 2019 hendrycks/robustness

Then we propose a new dataset called ImageNet-P which enables researchers to benchmark a classifier's robustness to common perturbations.

ADVERSARIAL DEFENSE DOMAIN GENERALIZATION

Theoretically Principled Trade-off between Robustness and Accuracy

24 Jan 2019yaodongyu/TRADES

We identify a trade-off between robustness and accuracy that serves as a guiding principle in the design of defenses against adversarial examples.

ADVERSARIAL ATTACK ADVERSARIAL DEFENSE