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Adversarial Defense

25 papers with code · Adversarial

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Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

ICLR 2019 Dan Hendrycks et al

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

ADVERSARIAL DEFENSE

01 May 2019

Featurized Bidirectional GAN: Adversarial Defense via Adversarially Learned Semantic Inference

ICLR 2019 Ruying Bao et al

In this paper, we propose a defense method, Featurized Bidirectional Generative Adversarial Networks (FBGAN), to extract the semantic features of the input and filter the non-semantic perturbation.

ADVERSARIAL DEFENSE

01 May 2019

EFFICIENT TWO-STEP ADVERSARIAL DEFENSE FOR DEEP NEURAL NETWORKS

ICLR 2019 Ting-Jui Chang et al

However, the computational cost of theadversarial training with PGD and other multi-step adversarial examples is muchhigher than that of the adversarial training with other simpler attack techniques. In this paper, we show how strong adversarial examples can be generated only ata cost similar to that of two runs of the fast gradient sign method (FGSM), allowing defense against adversarial attacks with a robustness level comparable to thatof the adversarial training with multi-step adversarial examples.

ADVERSARIAL DEFENSE

01 May 2019

Pixel Redrawn For A Robust Adversarial Defense

ICLR 2019 Jiacang Ho et al

Recently, an adversarial example becomes a serious problem to be aware of because it can fool trained neural networks easily.

ADVERSARIAL DEFENSE

01 May 2019

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

Characterizing Audio Adversarial Examples Using Temporal Dependency

ICLR 2019 Zhuolin 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 SPEECH RECOGNITION

01 May 2019

Adversarial Defense Through Network Profiling Based Path Extraction

17 Apr 2019Yuxian Qiu et al

Recently, researchers have started decomposing deep neural network models according to their semantics or functions.

ADVERSARIAL DEFENSE

17 Apr 2019

Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks

1 Apr 2019Aamir Mustafa et al

Deep neural networks are vulnerable to adversarial attacks, which can fool them by adding minuscule perturbations to the input images.

ADVERSARIAL DEFENSE

01 Apr 2019

L 1-norm double backpropagation adversarial defense

5 Mar 2019Ismaïla Seck et al

Adversarial examples are a challenging open problem for deep neural networks.

ADVERSARIAL DEFENSE

05 Mar 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