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1705.09554
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Robustness of classifiers to universal perturbations: a geometric perspective
26 May 2017
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
Omar Fawzi
P. Frossard
Stefano Soatto
AAML
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Papers citing
"Robustness of classifiers to universal perturbations: a geometric perspective"
50 / 63 papers shown
Origins of Low-dimensional Adversarial Perturbations
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Elvis Dohmatob
Chuan Guo
Morgane Goibert
AAML
199
4
0
25 Mar 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes
Elvis Dohmatob
A. Bietti
AAML
355
15
0
22 Mar 2022
On Distinctive Properties of Universal Perturbations
Sung Min Park
K. Wei
Kai Y. Xiao
Jungshian Li
Aleksander Madry
AAML
201
2
0
31 Dec 2021
On the Security & Privacy in Federated Learning
Gorka Abad
S. Picek
Víctor Julio Ramírez-Durán
A. Urbieta
317
12
0
10 Dec 2021
Improving Local Effectiveness for Global robust training
Jingyue Lu
M. P. Kumar
AAML
132
0
0
26 Oct 2021
Advances in adversarial attacks and defenses in computer vision: A survey
Naveed Akhtar
Lin Wang
Navid Kardan
M. Shah
AAML
467
298
0
01 Aug 2021
Attack to Fool and Explain Deep Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Naveed Akhtar
M. Jalwana
Bennamoun
Lin Wang
AAML
218
35
0
20 Jun 2021
Group-Structured Adversarial Training
Farzan Farnia
Amirali Aghazadeh
James Zou
David Tse
AAML
257
0
0
18 Jun 2021
Universal Adversarial Training with Class-Wise Perturbations
IEEE International Conference on Multimedia and Expo (ICME), 2021
Philipp Benz
Chaoning Zhang
Adil Karjauv
In So Kweon
AAML
187
28
0
07 Apr 2021
A Survey On Universal Adversarial Attack
International Joint Conference on Artificial Intelligence (IJCAI), 2021
Chaoning Zhang
Philipp Benz
Chenguo Lin
Adil Karjauv
Jing Wu
In So Kweon
AAML
315
105
0
02 Mar 2021
Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards A Fourier Perspective
AAAI Conference on Artificial Intelligence (AAAI), 2021
Chaoning Zhang
Philipp Benz
Adil Karjauv
In So Kweon
AAML
219
47
0
12 Feb 2021
Analysis of Dominant Classes in Universal Adversarial Perturbations
Knowledge-Based Systems (KBS), 2020
Jon Vadillo
Roberto Santana
Jose A. Lozano
AAML
217
9
0
28 Dec 2020
TrojanZoo: Towards Unified, Holistic, and Practical Evaluation of Neural Backdoors
European Symposium on Security and Privacy (EuroS&P), 2020
Ren Pang
Zheng Zhang
Xiangshan Gao
Zhaohan Xi
S. Ji
Peng Cheng
Xiapu Luo
Ting Wang
AAML
362
45
0
16 Dec 2020
Achieving Adversarial Robustness Requires An Active Teacher
Journal of Computational Mathematics (JCM), 2020
Chao Ma
Lexing Ying
142
1
0
14 Dec 2020
A Targeted Universal Attack on Graph Convolutional Network
Neural Processing Letters (NPL), 2020
Jiazhu Dai
Weifeng Zhu
Xiangfeng Luo
AAML
GNN
116
24
0
29 Nov 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective
ACM Computing Surveys (ACM CSUR), 2020
G. R. Machado
Eugênio Silva
R. Goldschmidt
AAML
248
182
0
08 Sep 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey
ACM Computing Surveys (ACM CSUR), 2020
A. Serban
E. Poll
Joost Visser
AAML
417
80
0
07 Aug 2020
Black-box Adversarial Sample Generation Based on Differential Evolution
Journal of Systems and Software (JSS), 2020
Junyu Lin
Lei Xu
Yingqi Liu
Xinming Zhang
AAML
127
36
0
30 Jul 2020
Understanding Adversarial Examples from the Mutual Influence of Images and Perturbations
Computer Vision and Pattern Recognition (CVPR), 2020
Chaoning Zhang
Philipp Benz
Tooba Imtiaz
In-So Kweon
SSL
AAML
178
134
0
13 Jul 2020
Classifier-independent Lower-Bounds for Adversarial Robustness
Elvis Dohmatob
364
1
0
17 Jun 2020
On Universalized Adversarial and Invariant Perturbations
Sandesh Kamath
Amit Deshpande
K. Subrahmanyam
AAML
60
0
0
08 Jun 2020
Universalization of any adversarial attack using very few test examples
Sandesh Kamath
Amit Deshpande
K. Subrahmanyam
Vineeth N. Balasubramanian
FedML
AAML
81
1
0
18 May 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness
Computer Vision and Pattern Recognition (CVPR), 2020
Ahmadreza Jeddi
M. Shafiee
Michelle Karg
C. Scharfenberger
A. Wong
OOD
AAML
365
72
0
02 Mar 2020
Challenges and Countermeasures for Adversarial Attacks on Deep Reinforcement Learning
IEEE Transactions on Artificial Intelligence (IEEE TAI), 2020
Inaam Ilahi
Muhammad Usama
Junaid Qadir
M. Janjua
Ala I. Al-Fuqaha
D. Hoang
Dusit Niyato
AAML
299
177
0
27 Jan 2020
Practical Fast Gradient Sign Attack against Mammographic Image Classifier
Ibrahim Yilmaz
AAML
163
11
0
27 Jan 2020
A Method for Computing Class-wise Universal Adversarial Perturbations
Tejus Gupta
Abhishek Sinha
Nupur Kumari
M. Singh
Balaji Krishnamurthy
AAML
91
11
0
01 Dec 2019
Indirect Local Attacks for Context-aware Semantic Segmentation Networks
European Conference on Computer Vision (ECCV), 2019
Krishna Kanth Nakka
Mathieu Salzmann
SSeg
AAML
200
33
0
29 Nov 2019
Universal adversarial examples in speech command classification
Jon Vadillo
Roberto Santana
AAML
200
30
0
22 Nov 2019
A Tale of Evil Twins: Adversarial Inputs versus Poisoned Models
Ren Pang
Hua Shen
Xinyang Zhang
S. Ji
Yevgeniy Vorobeychik
Xiaopu Luo
Alex Liu
Ting Wang
AAML
224
2
0
05 Nov 2019
Universal Adversarial Perturbation for Text Classification
Hang Gao
Tim Oates
AAML
164
15
0
10 Oct 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
International Journal of Automation and Computing (IJAC), 2019
Han Xu
Yao Ma
Haochen Liu
Debayan Deb
Hui Liu
Shucheng Zhou
Anil K. Jain
AAML
323
728
0
17 Sep 2019
Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors
Computer Vision and Pattern Recognition (CVPR), 2019
Gilad Cohen
Guillermo Sapiro
Raja Giryes
TDI
220
135
0
15 Sep 2019
Defending Against Adversarial Attacks by Suppressing the Largest Eigenvalue of Fisher Information Matrix
Yaxin Peng
Chaomin Shen
Guixu Zhang
Jinsong Fan
AAML
131
13
0
13 Sep 2019
Global Adversarial Attacks for Assessing Deep Learning Robustness
Hanbin Hu
Mitt Shah
Jianhua Z. Huang
Peng Li
AAML
166
4
0
19 Jun 2019
Defending Against Universal Attacks Through Selective Feature Regeneration
Tejas S. Borkar
Felix Heide
Lina Karam
AAML
221
1
0
08 Jun 2019
Label Universal Targeted Attack
Naveed Akhtar
M. Jalwana
Bennamoun
Lin Wang
AAML
134
5
0
27 May 2019
Adaptive Gradient for Adversarial Perturbations Generation
Yatie Xiao
Chi-Man Pun
ODL
172
10
0
01 Feb 2019
A Black-box Attack on Neural Networks Based on Swarm Evolutionary Algorithm
Xiaolei Liu
Yuheng Luo
Xiaosong Zhang
Qingxin Zhu
AAML
111
17
0
26 Jan 2019
Dissociable neural representations of adversarially perturbed images in convolutional neural networks and the human brain
Chi Zhang
Xiaohan Duan
Linyuan Wang
Yongli Li
Bin Yan
Guoen Hu
Ruyuan Zhang
Li Tong
AAML
177
1
0
22 Dec 2018
Universal Adversarial Training
A. Mendrik
Mahyar Najibi
Zheng Xu
John P. Dickerson
L. Davis
Tom Goldstein
AAML
OOD
238
203
0
27 Nov 2018
Deep Neural Network Concepts for Background Subtraction: A Systematic Review and Comparative Evaluation
T. Bouwmans
S. Javed
M. Sultana
Soon Ki Jung
199
328
0
13 Nov 2018
A Geometric Perspective on the Transferability of Adversarial Directions
International Conference on Artificial Intelligence and Statistics (AISTATS), 2018
Duncan C. McElfresh
H. Bidkhori
Dimitris Papailiopoulos
AAML
95
17
0
08 Nov 2018
The Adversarial Attack and Detection under the Fisher Information Metric
Chenxiao Zhao
P. T. Fletcher
Mixue Yu
Chaomin Shen
Guixu Zhang
Yaxin Peng
AAML
197
50
0
09 Oct 2018
Efficient Two-Step Adversarial Defense for Deep Neural Networks
Ting-Jui Chang
Yukun He
Peng Li
AAML
131
12
0
08 Oct 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon
A. Serban
E. Poll
Joost Visser
SILM
AAML
220
49
0
02 Oct 2018
Bridging machine learning and cryptography in defence against adversarial attacks
O. Taran
Shideh Rezaeifar
Svyatoslav Voloshynovskiy
AAML
124
24
0
05 Sep 2018
Are You Tampering With My Data?
Michele Alberti
Vinaychandran Pondenkandath
Marcel Würsch
Manuel Bouillon
Mathias Seuret
Rolf Ingold
Marcus Liwicki
AAML
168
20
0
21 Aug 2018
With Friends Like These, Who Needs Adversaries?
Saumya Jetley
Nicholas A. Lord
Juil Sock
AAML
282
72
0
11 Jul 2018
Built-in Vulnerabilities to Imperceptible Adversarial Perturbations
T. Tanay
Jerone T. A. Andrews
Lewis D. Griffin
156
7
0
19 Jun 2018
An Explainable Adversarial Robustness Metric for Deep Learning Neural Networks
Chirag Agarwal
Bo Dong
Dan Schonfeld
A. Hoogs
175
2
0
05 Jun 2018
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