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Adversarial Defense

19 papers with code · Adversarial

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Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network

ICLR 2019 Xuanqing Liu et al

Instead, we model randomness under the framework of Bayesian Neural Network (BNN) to formally learn the posterior distribution of models in a scalable way.

ADVERSARIAL DEFENSE

01 May 2019

PPD: Permutation Phase Defense Against Adversarial Examples in Deep Learning

25 Dec 2018Mehdi Jafarnia-Jahromi et al

In this paper, Permutation Phase Defense (PPD), is proposed as a novel method to resist adversarial attacks.

ADVERSARIAL DEFENSE

25 Dec 2018

Adversarial Defense by Stratified Convolutional Sparse Coding

30 Nov 2018Bo Sun et al

We propose an adversarial defense method that achieves state-of-the-art performance among attack-agnostic adversarial defense methods while also maintaining robustness to input resolution, scale of adversarial perturbation, and scale of dataset size.

ADVERSARIAL DEFENSE

30 Nov 2018

EnResNet: ResNet Ensemble via the Feynman-Kac Formalism

26 Nov 2018Bao Wang et al

We propose a simple yet powerful ResNet ensemble algorithm which consists of two components: First, we modify the base ResNet by adding variance specified Gaussian noise to the output of each original residual mapping.

ADVERSARIAL ATTACK ADVERSARIAL DEFENSE

26 Nov 2018

Attention, Please! Adversarial Defense via Attention Rectification and Preservation

24 Nov 2018Shangxi Wu et al

This study provides a new understanding of the adversarial attack problem by examining the correlation between adversarial attack and visual attention change.

ADVERSARIAL ATTACK ADVERSARIAL DEFENSE

24 Nov 2018

MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense

20 Nov 2018Rushil Anirudh et al

Solving inverse problems continues to be a central challenge in computer vision.

ADVERSARIAL DEFENSE

20 Nov 2018

Efficient Two-Step Adversarial Defense for Deep Neural Networks

ICLR 2019 Ting-Jui Chang et al

However, the computational cost of the adversarial training with PGD and other multi-step adversarial examples is much higher than that of the adversarial training with other simpler attack techniques.

ADVERSARIAL DEFENSE

08 Oct 2018

Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network

ICLR 2019 Xuanqing Liu et al

Instead, we model randomness under the framework of Bayesian Neural Network (BNN) to formally learn the posterior distribution of models in a scalable way.

ADVERSARIAL DEFENSE

01 Oct 2018

Characterizing Audio Adversarial Examples Using Temporal Dependency

28 Sep 2018Zhuolin Yang et al

In particular, our results reveal the importance of using the temporal dependency in audio data to gain discriminate power against adversarial examples.

ADVERSARIAL DEFENSE

28 Sep 2018

Adversarial Defense via Data Dependent Activation Function and Total Variation Minimization

23 Sep 2018Bao Wang et al

We improve the robustness of deep neural nets to adversarial attacks by using an interpolating function as the output activation.

ADVERSARIAL DEFENSE

23 Sep 2018