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DeepFool: a simple and accurate method to fool deep neural networks

DeepFool: a simple and accurate method to fool deep neural networks

14 November 2015
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
    AAML
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Papers citing "DeepFool: a simple and accurate method to fool deep neural networks"

20 / 870 papers shown
Title
MTDeep: Boosting the Security of Deep Neural Nets Against Adversarial
  Attacks with Moving Target Defense
MTDeep: Boosting the Security of Deep Neural Nets Against Adversarial Attacks with Moving Target Defense
Sailik Sengupta
Tathagata Chakraborti
S. Kambhampati
AAML
26
63
0
19 May 2017
Ensemble Adversarial Training: Attacks and Defenses
Ensemble Adversarial Training: Attacks and Defenses
Florian Tramèr
Alexey Kurakin
Nicolas Papernot
Ian Goodfellow
Dan Boneh
Patrick McDaniel
AAML
65
2,699
0
19 May 2017
DeepCorrect: Correcting DNN models against Image Distortions
DeepCorrect: Correcting DNN models against Image Distortions
Tejas S. Borkar
Lina Karam
24
93
0
05 May 2017
Parseval Networks: Improving Robustness to Adversarial Examples
Parseval Networks: Improving Robustness to Adversarial Examples
Moustapha Cissé
Piotr Bojanowski
Edouard Grave
Yann N. Dauphin
Nicolas Usunier
AAML
86
798
0
28 Apr 2017
Universal Adversarial Perturbations Against Semantic Image Segmentation
Universal Adversarial Perturbations Against Semantic Image Segmentation
J. H. Metzen
Mummadi Chaithanya Kumar
Thomas Brox
Volker Fischer
AAML
30
287
0
19 Apr 2017
The Space of Transferable Adversarial Examples
The Space of Transferable Adversarial Examples
Florian Tramèr
Nicolas Papernot
Ian Goodfellow
Dan Boneh
Patrick McDaniel
AAML
SILM
35
555
0
11 Apr 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural
  Networks
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
Weilin Xu
David Evans
Yanjun Qi
AAML
25
1,233
0
04 Apr 2017
Adversarial Image Perturbation for Privacy Protection -- A Game Theory
  Perspective
Adversarial Image Perturbation for Privacy Protection -- A Game Theory Perspective
Seong Joon Oh
Mario Fritz
Bernt Schiele
CVBM
AAML
339
160
0
28 Mar 2017
Blocking Transferability of Adversarial Examples in Black-Box Learning
  Systems
Blocking Transferability of Adversarial Examples in Black-Box Learning Systems
Hossein Hosseini
Yize Chen
Sreeram Kannan
Baosen Zhang
Radha Poovendran
AAML
30
106
0
13 Mar 2017
Tactics of Adversarial Attack on Deep Reinforcement Learning Agents
Tactics of Adversarial Attack on Deep Reinforcement Learning Agents
Yen-Chen Lin
Zhang-Wei Hong
Yuan-Hong Liao
Meng-Li Shih
Ming Liu
Min Sun
AAML
17
411
0
08 Mar 2017
Compositional Falsification of Cyber-Physical Systems with Machine
  Learning Components
Compositional Falsification of Cyber-Physical Systems with Machine Learning Components
T. Dreossi
Alexandre Donzé
S. Seshia
AAML
32
230
0
02 Mar 2017
Simple Black-Box Adversarial Perturbations for Deep Networks
Simple Black-Box Adversarial Perturbations for Deep Networks
Nina Narodytska
S. Kasiviswanathan
AAML
21
237
0
19 Dec 2016
Universal adversarial perturbations
Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
Omar Fawzi
P. Frossard
AAML
29
2,514
0
26 Oct 2016
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
Marta Kwiatkowska
Sen Wang
Min Wu
AAML
183
933
0
21 Oct 2016
Robustness of classifiers: from adversarial to random noise
Robustness of classifiers: from adversarial to random noise
Alhussein Fawzi
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
AAML
13
367
0
31 Aug 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
71
8,460
0
16 Aug 2016
Towards Verified Artificial Intelligence
Towards Verified Artificial Intelligence
S. Seshia
Dorsa Sadigh
S. Shankar Sastry
20
203
0
27 Jun 2016
Measuring Neural Net Robustness with Constraints
Measuring Neural Net Robustness with Constraints
Osbert Bastani
Yani Andrew Ioannou
Leonidas Lampropoulos
Dimitrios Vytiniotis
A. Nori
A. Criminisi
AAML
17
422
0
24 May 2016
Analysis of classifiers' robustness to adversarial perturbations
Analysis of classifiers' robustness to adversarial perturbations
Alhussein Fawzi
Omar Fawzi
P. Frossard
AAML
35
361
0
09 Feb 2015
MatConvNet - Convolutional Neural Networks for MATLAB
MatConvNet - Convolutional Neural Networks for MATLAB
Andrea Vedaldi
Karel Lenc
183
2,946
0
15 Dec 2014
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