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Countering Adversarial Images using Input Transformations

Countering Adversarial Images using Input Transformations

31 October 2017
Chuan Guo
Mayank Rana
Moustapha Cissé
Laurens van der Maaten
    AAML
ArXivPDFHTML

Papers citing "Countering Adversarial Images using Input Transformations"

50 / 316 papers shown
Title
Towards Adversarially Robust Object Detection
Towards Adversarially Robust Object Detection
Haichao Zhang
Jianyu Wang
AAML
ObjD
23
130
0
24 Jul 2019
Evolving Robust Neural Architectures to Defend from Adversarial Attacks
Evolving Robust Neural Architectures to Defend from Adversarial Attacks
Shashank Kotyan
Danilo Vasconcellos Vargas
OOD
AAML
24
36
0
27 Jun 2019
Defending Adversarial Attacks by Correcting logits
Defending Adversarial Attacks by Correcting logits
Yifeng Li
Lingxi Xie
Ya Zhang
Rui Zhang
Yanfeng Wang
Qi Tian
AAML
29
5
0
26 Jun 2019
Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case
  Study on CNN-Based Lithographic Hotspot Detection
Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection
Kang Liu
Haoyu Yang
Yuzhe Ma
Benjamin Tan
Bei Yu
Evangeline F. Y. Young
Ramesh Karri
S. Garg
AAML
20
10
0
25 Jun 2019
Defending Against Adversarial Attacks Using Random Forests
Defending Against Adversarial Attacks Using Random Forests
Yifan Ding
Liqiang Wang
Huan Zhang
Jinfeng Yi
Deliang Fan
Boqing Gong
AAML
21
14
0
16 Jun 2019
Towards Stable and Efficient Training of Verifiably Robust Neural
  Networks
Towards Stable and Efficient Training of Verifiably Robust Neural Networks
Huan Zhang
Hongge Chen
Chaowei Xiao
Sven Gowal
Robert Stanforth
Bo-wen Li
Duane S. Boning
Cho-Jui Hsieh
AAML
17
344
0
14 Jun 2019
Enhancing Gradient-based Attacks with Symbolic Intervals
Enhancing Gradient-based Attacks with Symbolic Intervals
Shiqi Wang
Yizheng Chen
Ahmed Abdou
Suman Jana
AAML
31
15
0
05 Jun 2019
Adversarial Examples for Edge Detection: They Exist, and They Transfer
Adversarial Examples for Edge Detection: They Exist, and They Transfer
Christian Cosgrove
Alan Yuille
AAML
GAN
22
12
0
02 Jun 2019
Enhancing Transformation-based Defenses using a Distribution Classifier
Enhancing Transformation-based Defenses using a Distribution Classifier
C. Kou
H. Lee
E. Chang
Teck Khim Ng
37
3
0
01 Jun 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by
  Adversarial Machine Learning and The Way Forward
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward
A. Qayyum
Muhammad Usama
Junaid Qadir
Ala I. Al-Fuqaha
AAML
27
187
0
29 May 2019
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
Yuzhe Yang
Guo Zhang
Dina Katabi
Zhi Xu
AAML
15
168
0
28 May 2019
Purifying Adversarial Perturbation with Adversarially Trained
  Auto-encoders
Purifying Adversarial Perturbation with Adversarially Trained Auto-encoders
Hebi Li
Qi Xiao
Shixin Tian
Jin Tian
AAML
24
4
0
26 May 2019
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
38
0
0
23 May 2019
ROSA: Robust Salient Object Detection against Adversarial Attacks
ROSA: Robust Salient Object Detection against Adversarial Attacks
Haofeng Li
Guanbin Li
Yizhou Yu
AAML
16
28
0
09 May 2019
Adversarial Training for Free!
Adversarial Training for Free!
Ali Shafahi
Mahyar Najibi
Amin Ghiasi
Zheng Xu
John P. Dickerson
Christoph Studer
L. Davis
Gavin Taylor
Tom Goldstein
AAML
68
1,231
0
29 Apr 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
Adversarial Defense by Restricting the Hidden Space of Deep Neural
  Networks
Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks
Aamir Mustafa
Salman Khan
Munawar Hayat
Roland Göcke
Jianbing Shen
Ling Shao
AAML
17
151
0
01 Apr 2019
On the Vulnerability of CNN Classifiers in EEG-Based BCIs
On the Vulnerability of CNN Classifiers in EEG-Based BCIs
Xiao Zhang
Dongrui Wu
AAML
24
82
0
31 Mar 2019
Defending against Whitebox Adversarial Attacks via Randomized
  Discretization
Defending against Whitebox Adversarial Attacks via Randomized Discretization
Yuchen Zhang
Percy Liang
AAML
32
75
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
42
19
0
15 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
19
20
0
28 Feb 2019
Adversarial Attack and Defense on Point Sets
Adversarial Attack and Defense on Point Sets
Jiancheng Yang
Qiang Zhang
Rongyao Fang
Bingbing Ni
Jinxian Liu
Qi Tian
3DPC
24
122
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
Disentangled Deep Autoencoding Regularization for Robust Image
  Classification
Disentangled Deep Autoencoding Regularization for Robust Image Classification
Zhenyu Duan
Martin Renqiang Min
Erran L. Li
Mingbo Cai
Yi Tian Xu
Bingbing Ni
16
2
0
27 Feb 2019
Robustness Of Saak Transform Against Adversarial Attacks
Robustness Of Saak Transform Against Adversarial Attacks
T. Ramanathan
Abinaya Manimaran
Suya You
C.-C. Jay Kuo
28
5
0
07 Feb 2019
Adversarial Examples Are a Natural Consequence of Test Error in Noise
Adversarial Examples Are a Natural Consequence of Test Error in Noise
Nic Ford
Justin Gilmer
Nicholas Carlini
E. D. Cubuk
AAML
36
318
0
29 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
Characterizing and evaluating adversarial examples for Offline
  Handwritten Signature Verification
Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification
L. G. Hafemann
R. Sabourin
Luiz Eduardo Soares de Oliveira
AAML
19
42
0
10 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
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
On the Security of Randomized Defenses Against Adversarial Samples
On the Security of Randomized Defenses Against Adversarial Samples
K. Sharad
G. Marson
H. Truong
Ghassan O. Karame
AAML
35
1
0
11 Dec 2018
Learning Transferable Adversarial Examples via Ghost Networks
Learning Transferable Adversarial Examples via Ghost Networks
Yingwei Li
S. Bai
Yuyin Zhou
Cihang Xie
Zhishuai Zhang
Alan Yuille
AAML
42
136
0
09 Dec 2018
Feature Denoising for Improving Adversarial Robustness
Feature Denoising for Improving Adversarial Robustness
Cihang Xie
Yuxin Wu
Laurens van der Maaten
Alan Yuille
Kaiming He
44
904
0
09 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
MixTrain: Scalable Training of Verifiably Robust Neural Networks
MixTrain: Scalable Training of Verifiably Robust Neural Networks
Yue Zhang
Yizheng Chen
Ahmed Abdou
Mohsen Guizani
AAML
27
23
0
06 Nov 2018
On Extensions of CLEVER: A Neural Network Robustness Evaluation
  Algorithm
On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm
Tsui-Wei Weng
Huan Zhang
Pin-Yu Chen
A. Lozano
Cho-Jui Hsieh
Luca Daniel
28
10
0
19 Oct 2018
Query-Efficient Black-Box Attack by Active Learning
Query-Efficient Black-Box Attack by Active Learning
Pengcheng Li
Jinfeng Yi
Lijun Zhang
AAML
MLAU
21
54
0
13 Sep 2018
On the Structural Sensitivity of Deep Convolutional Networks to the
  Directions of Fourier Basis Functions
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions
Yusuke Tsuzuku
Issei Sato
AAML
24
62
0
11 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
A Simple Unified Framework for Detecting Out-of-Distribution Samples and
  Adversarial Attacks
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
Kimin Lee
Kibok Lee
Honglak Lee
Jinwoo Shin
OODD
23
2,008
0
10 Jul 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
31
17
0
08 Jun 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
Detecting Adversarial Samples for Deep Neural Networks through Mutation
  Testing
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing
Jingyi Wang
Jun Sun
Peixin Zhang
Xinyu Wang
AAML
21
41
0
14 May 2018
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