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Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using
  Generative Models

Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models

17 May 2018
Pouya Samangouei
Maya Kabkab
Rama Chellappa
    AAML
    GAN
ArXivPDFHTML

Papers citing "Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models"

50 / 252 papers shown
Title
Enhancing Adversarial Defense by k-Winners-Take-All
Enhancing Adversarial Defense by k-Winners-Take-All
Chang Xiao
Peilin Zhong
Changxi Zheng
AAML
24
97
0
25 May 2019
Thwarting finite difference adversarial attacks with output
  randomization
Thwarting finite difference adversarial attacks with output randomization
Haidar Khan
Daniel Park
Azer Khan
B. Yener
SILM
AAML
41
0
0
23 May 2019
What Do Adversarially Robust Models Look At?
What Do Adversarially Robust Models Look At?
Takahiro Itazuri
Yoshihiro Fukuhara
Hirokatsu Kataoka
Shigeo Morishima
19
5
0
19 May 2019
Adversarial Defense Through Network Profiling Based Path Extraction
Adversarial Defense Through Network Profiling Based Path Extraction
Yuxian Qiu
Jingwen Leng
Cong Guo
Quan Chen
Chong Li
Minyi Guo
Yuhao Zhu
AAML
24
51
0
17 Apr 2019
Evading Defenses to Transferable Adversarial Examples by
  Translation-Invariant Attacks
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks
Yinpeng Dong
Tianyu Pang
Hang Su
Jun Zhu
SILM
AAML
49
830
0
05 Apr 2019
Bridging Adversarial Robustness and Gradient Interpretability
Bridging Adversarial Robustness and Gradient Interpretability
Beomsu Kim
Junghoon Seo
Taegyun Jeon
AAML
22
39
0
27 Mar 2019
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial
  Robustness
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness
J. Jacobsen
Jens Behrmann
Nicholas Carlini
Florian Tramèr
Nicolas Papernot
AAML
24
46
0
25 Mar 2019
Variational Inference with Latent Space Quantization for Adversarial
  Resilience
Variational Inference with Latent Space Quantization for Adversarial Resilience
Vinay Kyatham
P. PrathoshA.
Tarun Kumar Yadav
Deepak Mishra
Dheeraj Mundhra
AAML
19
3
0
24 Mar 2019
On Certifying Non-uniform Bound against Adversarial Attacks
On Certifying Non-uniform Bound against Adversarial Attacks
Chen Liu
Ryota Tomioka
V. Cevher
AAML
50
19
0
15 Mar 2019
Adversarial Out-domain Examples for Generative Models
Adversarial Out-domain Examples for Generative Models
Dario Pasquini
Marco Mingione
M. Bernaschi
WIGM
SILM
AAML
23
6
0
07 Mar 2019
Defense Against Adversarial Images using Web-Scale Nearest-Neighbor
  Search
Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search
Abhimanyu Dubey
Laurens van der Maaten
Zeki Yalniz
Yixuan Li
D. Mahajan
AAML
33
64
0
05 Mar 2019
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial
  Perturbations
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations
Saeid Asgari Taghanaki
Kumar Abhishek
Shekoofeh Azizi
Ghassan Hamarneh
AAML
31
40
0
03 Mar 2019
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional
  GAN
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN
Ke Sun
Zhanxing Zhu
Zhouchen Lin
AAML
24
20
0
28 Feb 2019
Robust Decision Trees Against Adversarial Examples
Robust Decision Trees Against Adversarial Examples
Hongge Chen
Huan Zhang
Duane S. Boning
Cho-Jui Hsieh
AAML
31
116
0
27 Feb 2019
GAN- vs. JPEG2000 Image Compression for Distributed Automotive
  Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation
GAN- vs. JPEG2000 Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation
Jonas Löhdefink
Andreas Bär
Nico M. Schmidt
Fabian Hüger
Peter Schlicht
Tim Fingscheidt
29
15
0
12 Feb 2019
Collaborative Sampling in Generative Adversarial Networks
Collaborative Sampling in Generative Adversarial Networks
Yuejiang Liu
Parth Kothari
Alexandre Alahi
TTA
30
16
0
02 Feb 2019
Action Robust Reinforcement Learning and Applications in Continuous
  Control
Action Robust Reinforcement Learning and Applications in Continuous Control
Chen Tessler
Yonathan Efroni
Shie Mannor
30
230
0
26 Jan 2019
The Limitations of Adversarial Training and the Blind-Spot Attack
The Limitations of Adversarial Training and the Blind-Spot Attack
Huan Zhang
Hongge Chen
Zhao Song
Duane S. Boning
Inderjit S. Dhillon
Cho-Jui Hsieh
AAML
22
144
0
15 Jan 2019
Image Super-Resolution as a Defense Against Adversarial Attacks
Image Super-Resolution as a Defense Against Adversarial Attacks
Aamir Mustafa
Salman H. Khan
Munawar Hayat
Jianbing Shen
Ling Shao
AAML
SupR
27
168
0
07 Jan 2019
Face Recognition: A Novel Multi-Level Taxonomy based Survey
Face Recognition: A Novel Multi-Level Taxonomy based Survey
Alireza Sepas-Moghaddam
F. Pereira
P. Correia
CVBM
19
46
0
03 Jan 2019
Adversarial Attack and Defense on Graph Data: A Survey
Adversarial Attack and Defense on Graph Data: A Survey
Lichao Sun
Yingtong Dou
Carl Yang
Ji Wang
Yixin Liu
Philip S. Yu
Lifang He
Yangqiu Song
GNN
AAML
23
275
0
26 Dec 2018
Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks
Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks
Xiang Li
Shihao Ji
AAML
27
26
0
17 Dec 2018
Thwarting Adversarial Examples: An $L_0$-RobustSparse Fourier Transform
Thwarting Adversarial Examples: An L0L_0L0​-RobustSparse Fourier Transform
Mitali Bafna
Jack Murtagh
Nikhil Vyas
AAML
13
48
0
12 Dec 2018
AutoGAN: Robust Classifier Against Adversarial Attacks
AutoGAN: Robust Classifier Against Adversarial Attacks
Blerta Lindqvist
Shridatt Sugrim
R. Izmailov
AAML
29
7
0
08 Dec 2018
Mathematical Analysis of Adversarial Attacks
Mathematical Analysis of Adversarial Attacks
Zehao Dou
Stanley J. Osher
Bao Wang
AAML
24
18
0
15 Nov 2018
QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural
  Network against Adversarial Attacks
QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks
Faiq Khalid
Hassan Ali
Hammad Tariq
Muhammad Abdullah Hanif
Semeen Rehman
Rehan Ahmed
Mohamed Bennai
AAML
MQ
35
37
0
04 Nov 2018
Learning to Defend by Learning to Attack
Learning to Defend by Learning to Attack
Haoming Jiang
Zhehui Chen
Yuyang Shi
Bo Dai
T. Zhao
21
22
0
03 Nov 2018
Efficient Two-Step Adversarial Defense for Deep Neural Networks
Efficient Two-Step Adversarial Defense for Deep Neural Networks
Ting-Jui Chang
Yukun He
Peng Li
AAML
25
11
0
08 Oct 2018
Generating 3D Adversarial Point Clouds
Generating 3D Adversarial Point Clouds
Chong Xiang
C. Qi
Bo-wen Li
3DPC
24
286
0
19 Sep 2018
Metamorphic Relation Based Adversarial Attacks on Differentiable Neural
  Computer
Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer
Alvin Chan
Lei Ma
Felix Juefei Xu
Xiaofei Xie
Yang Liu
Yew-Soon Ong
OOD
AAML
22
17
0
07 Sep 2018
DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided
  Fuzzing
DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing
Xiaofei Xie
Lei Ma
Felix Juefei Xu
Hongxu Chen
Minhui Xue
Bo-wen Li
Yang Liu
Jianjun Zhao
Jianxiong Yin
Simon See
43
40
0
04 Sep 2018
Motivating the Rules of the Game for Adversarial Example Research
Motivating the Rules of the Game for Adversarial Example Research
Justin Gilmer
Ryan P. Adams
Ian Goodfellow
David G. Andersen
George E. Dahl
AAML
50
226
0
18 Jul 2018
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal
  Transport and Diffusions
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions
Antoine Liutkus
Umut Simsekli
Szymon Majewski
Alain Durmus
Fabian-Robert Stöter
DiffM
35
120
0
21 Jun 2018
Hardware Trojan Attacks on Neural Networks
Hardware Trojan Attacks on Neural Networks
Joseph Clements
Yingjie Lao
AAML
27
89
0
14 Jun 2018
Monge blunts Bayes: Hardness Results for Adversarial Training
Monge blunts Bayes: Hardness Results for Adversarial Training
Zac Cranko
A. Menon
Richard Nock
Cheng Soon Ong
Zhan Shi
Christian J. Walder
AAML
34
17
0
08 Jun 2018
Resisting Adversarial Attacks using Gaussian Mixture Variational
  Autoencoders
Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders
Partha Ghosh
Arpan Losalka
Michael J. Black
AAML
21
77
0
31 May 2018
Defending Against Adversarial Attacks by Leveraging an Entire GAN
Defending Against Adversarial Attacks by Leveraging an Entire GAN
G. Santhanam
Paulina Grnarova
AAML
16
40
0
27 May 2018
Performing Co-Membership Attacks Against Deep Generative Models
Performing Co-Membership Attacks Against Deep Generative Models
Kin Sum Liu
Chaowei Xiao
Bo-wen Li
Jie Gao
AAML
MIACV
24
58
0
24 May 2018
Towards the first adversarially robust neural network model on MNIST
Towards the first adversarially robust neural network model on MNIST
Lukas Schott
Jonas Rauber
Matthias Bethge
Wieland Brendel
AAML
OOD
14
369
0
23 May 2018
Featurized Bidirectional GAN: Adversarial Defense via Adversarially
  Learned Semantic Inference
Featurized Bidirectional GAN: Adversarial Defense via Adversarially Learned Semantic Inference
Ruying Bao
Sihang Liang
Qingcan Wang
GAN
AAML
24
13
0
21 May 2018
VectorDefense: Vectorization as a Defense to Adversarial Examples
VectorDefense: Vectorization as a Defense to Adversarial Examples
V. Kabilan
Brandon L. Morris
Anh Totti Nguyen
AAML
22
21
0
23 Apr 2018
Fortified Networks: Improving the Robustness of Deep Networks by
  Modeling the Manifold of Hidden Representations
Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations
Alex Lamb
Jonathan Binas
Anirudh Goyal
Dmitriy Serdyuk
Sandeep Subramanian
Ioannis Mitliagkas
Yoshua Bengio
OOD
34
43
0
07 Apr 2018
Adversarial Defense based on Structure-to-Signal Autoencoders
Adversarial Defense based on Structure-to-Signal Autoencoders
Joachim Folz
Sebastián M. Palacio
Jörn Hees
Damian Borth
Andreas Dengel
AAML
26
32
0
21 Mar 2018
Robust GANs against Dishonest Adversaries
Robust GANs against Dishonest Adversaries
Zhi Xu
Chengtao Li
Stefanie Jegelka
AAML
34
3
0
27 Feb 2018
Retrieval-Augmented Convolutional Neural Networks for Improved
  Robustness against Adversarial Examples
Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples
Jake Zhao
Kyunghyun Cho
AAML
24
20
0
26 Feb 2018
Adversarial vulnerability for any classifier
Adversarial vulnerability for any classifier
Alhussein Fawzi
Hamza Fawzi
Omar Fawzi
AAML
33
248
0
23 Feb 2018
Are Generative Classifiers More Robust to Adversarial Attacks?
Are Generative Classifiers More Robust to Adversarial Attacks?
Yingzhen Li
John Bradshaw
Yash Sharma
AAML
57
78
0
19 Feb 2018
A General Framework for Adversarial Examples with Objectives
A General Framework for Adversarial Examples with Objectives
Mahmood Sharif
Sruti Bhagavatula
Lujo Bauer
Michael K. Reiter
AAML
GAN
13
191
0
31 Dec 2017
The Robust Manifold Defense: Adversarial Training using Generative
  Models
The Robust Manifold Defense: Adversarial Training using Generative Models
A. Jalal
Andrew Ilyas
C. Daskalakis
A. Dimakis
AAML
31
174
0
26 Dec 2017
Generative Adversarial Perturbations
Generative Adversarial Perturbations
Omid Poursaeed
Isay Katsman
Bicheng Gao
Serge J. Belongie
AAML
GAN
WIGM
31
351
0
06 Dec 2017
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