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Adversarial Defense

25 papers with code · Adversarial

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Latest papers with code

A Provable Defense for Deep Residual Networks

29 Mar 2019eth-sri/diffai

We present a training system, which can provably defend significantly larger neural networks than previously possible, including ResNet-34 and DenseNet-100.

ADVERSARIAL DEFENSE

127
29 Mar 2019

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

98
28 Mar 2019

Wasserstein Adversarial Examples via Projected Sinkhorn Iterations

21 Feb 2019locuslab/projected_sinkhorn

In this paper, we propose a new threat model for adversarial attacks based on the Wasserstein distance.

ADVERSARIAL ATTACK ADVERSARIAL DEFENSE IMAGE CLASSIFICATION

27
21 Feb 2019

advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch

20 Feb 2019BorealisAI/advertorch

advertorch is a toolbox for adversarial robustness research.

ADVERSARIAL ATTACK ADVERSARIAL DEFENSE

160
20 Feb 2019

On Evaluating Adversarial Robustness

18 Feb 2019evaluating-adversarial-robustness/adv-eval-paper

Correctly evaluating defenses against adversarial examples has proven to be extremely difficult.

ADVERSARIAL ATTACK ADVERSARIAL DEFENSE

119
18 Feb 2019

Certified Adversarial Robustness via Randomized Smoothing

8 Feb 2019locuslab/smoothing

Recent work has shown that any classifier which classifies well under Gaussian noise can be leveraged to create a new classifier that is provably robust to adversarial perturbations in L2 norm.

ADVERSARIAL DEFENSE

33
08 Feb 2019

Image Super-Resolution as a Defense Against Adversarial Attacks

7 Jan 2019aamir-mustafa/super-resolution-adversarial-defense

The proposed scheme is simple and has the following advantages: (1) it does not require any model training or parameter optimization, (2) it complements other existing defense mechanisms, (3) it is agnostic to the attacked model and attack type and (4) it provides superior performance across all popular attack algorithms.

ADVERSARIAL DEFENSE IMAGE ENHANCEMENT IMAGE RESTORATION IMAGE SUPER-RESOLUTION

39
07 Jan 2019

Feature Denoising for Improving Adversarial Robustness

9 Dec 2018facebookresearch/ImageNet-Adversarial-Training

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

ADVERSARIAL DEFENSE IMAGE CLASSIFICATION

284
09 Dec 2018
1
07 Dec 2018