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DeepFool: a simple and accurate method to fool deep neural networks
v1v2v3 (latest)

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

14 November 2015
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
    AAML
ArXiv (abs)PDFHTML

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

50 / 2,353 papers shown
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
AAMLMQ
216
39
0
04 Nov 2018
TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep
  Neural Networks
TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks
Faiq Khalid
Muhammad Abdullah Hanif
Semeen Rehman
Rehan Ahmed
Mohamed Bennai
AAML
206
21
0
02 Nov 2018
Efficient Neural Network Robustness Certification with General
  Activation Functions
Efficient Neural Network Robustness Certification with General Activation Functions
Huan Zhang
Tsui-Wei Weng
Pin-Yu Chen
Cho-Jui Hsieh
Luca Daniel
AAML
379
843
0
02 Nov 2018
Stronger Data Poisoning Attacks Break Data Sanitization Defenses
Stronger Data Poisoning Attacks Break Data Sanitization Defenses
Pang Wei Koh
Jacob Steinhardt
Abigail Z. Jacobs
286
269
0
02 Nov 2018
Data Poisoning Attack against Unsupervised Node Embedding Methods
Data Poisoning Attack against Unsupervised Node Embedding Methods
Mingjie Sun
Jian Tang
Huichen Li
Yue Liu
Chaowei Xiao
Yao-Liang Chen
Basel Alomair
GNNAAML
155
69
0
30 Oct 2018
Improved Network Robustness with Adversary Critic
Improved Network Robustness with Adversary Critic
Alexander Matyasko
Lap-Pui Chau
AAML
93
14
0
30 Oct 2018
Adversarial Risk and Robustness: General Definitions and Implications
  for the Uniform Distribution
Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution
Dimitrios I. Diochnos
Saeed Mahloujifar
Mohammad Mahmoody
AAML
132
75
0
29 Oct 2018
Evading classifiers in discrete domains with provable optimality
  guarantees
Evading classifiers in discrete domains with provable optimality guarantees
B. Kulynych
Jamie Hayes
N. Samarin
Carmela Troncoso
AAML
241
21
0
25 Oct 2018
Robust Adversarial Learning via Sparsifying Front Ends
Robust Adversarial Learning via Sparsifying Front Ends
S. Gopalakrishnan
Zhinus Marzi
Metehan Cekic
Upamanyu Madhow
Ramtin Pedarsani
AAML
200
3
0
24 Oct 2018
Stochastic Substitute Training: A Gray-box Approach to Craft Adversarial
  Examples Against Gradient Obfuscation Defenses
Stochastic Substitute Training: A Gray-box Approach to Craft Adversarial Examples Against Gradient Obfuscation Defenses
Mohammad J. Hashemi
Greg Cusack
Eric Keller
AAMLSILM
119
9
0
23 Oct 2018
One Bit Matters: Understanding Adversarial Examples as the Abuse of
  Redundancy
One Bit Matters: Understanding Adversarial Examples as the Abuse of Redundancy
Jingkang Wang
R. Jia
Gerald Friedland
Yangqiu Song
C. Spanos
AAML
125
4
0
23 Oct 2018
Sparse DNNs with Improved Adversarial Robustness
Sparse DNNs with Improved Adversarial Robustness
Yiwen Guo
Chao Zhang
Changshui Zhang
Yurong Chen
AAML
212
165
0
23 Oct 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
114
13
0
19 Oct 2018
Provable Robustness of ReLU networks via Maximization of Linear Regions
Provable Robustness of ReLU networks via Maximization of Linear Regions
Francesco Croce
Maksym Andriushchenko
Matthias Hein
233
170
0
17 Oct 2018
Security Matters: A Survey on Adversarial Machine Learning
Security Matters: A Survey on Adversarial Machine Learning
Guofu Li
Pengjia Zhu
Jin Li
Zhemin Yang
Ning Cao
Zhiyi Chen
AAML
235
27
0
16 Oct 2018
Multi-scale Geometric Summaries for Similarity-based Sensor Fusion
Multi-scale Geometric Summaries for Similarity-based Sensor Fusion
Christopher J. Tralie
Paul Bendich
J. Harer
167
2
0
13 Oct 2018
MeshAdv: Adversarial Meshes for Visual Recognition
MeshAdv: Adversarial Meshes for Visual Recognition
Chaowei Xiao
Dawei Yang
Yue Liu
Gaowen Liu
M. Liu
AAML
184
26
0
11 Oct 2018
Secure Deep Learning Engineering: A Software Quality Assurance
  Perspective
Secure Deep Learning Engineering: A Software Quality Assurance Perspective
Lei Ma
Felix Juefei Xu
Minhui Xue
Q. Hu
Sen Chen
Yue Liu
Yang Liu
Jianjun Zhao
Jianxiong Yin
Simon See
AAML
137
37
0
10 Oct 2018
Analyzing the Noise Robustness of Deep Neural Networks
Analyzing the Noise Robustness of Deep Neural Networks
Mengchen Liu
Shixia Liu
Hang Su
Kelei Cao
Jun Zhu
AAML
127
9
0
09 Oct 2018
The Adversarial Attack and Detection under the Fisher Information Metric
The Adversarial Attack and Detection under the Fisher Information Metric
Chenxiao Zhao
P. T. Fletcher
Mixue Yu
Chaomin Shen
Guixu Zhang
Yaxin Peng
AAML
202
50
0
09 Oct 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
136
12
0
08 Oct 2018
Combinatorial Attacks on Binarized Neural Networks
Combinatorial Attacks on Binarized Neural Networks
Elias Boutros Khalil
Amrita Gupta
B. Dilkina
AAML
187
42
0
08 Oct 2018
Interpretable Convolutional Neural Networks via Feedforward Design
Interpretable Convolutional Neural Networks via Feedforward Design
C.-C. Jay Kuo
Min Zhang
Siyang Li
Jiali Duan
Yueru Chen
164
167
0
05 Oct 2018
Improved Generalization Bounds for Adversarially Robust Learning
Improved Generalization Bounds for Adversarially Robust Learning
Idan Attias
A. Kontorovich
Yishay Mansour
332
22
0
04 Oct 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon
Adversarial Examples - A Complete Characterisation of the Phenomenon
A. Serban
E. Poll
Joost Visser
SILMAAML
253
50
0
02 Oct 2018
Large batch size training of neural networks with adversarial training
  and second-order information
Large batch size training of neural networks with adversarial training and second-order information
Z. Yao
A. Gholami
Daiyaan Arfeen
Richard Liaw
Alfons Kemper
Kurt Keutzer
Michael W. Mahoney
ODL
288
46
0
02 Oct 2018
Improved robustness to adversarial examples using Lipschitz regularization of the loss
Chris Finlay
Adam M. Oberman
B. Abbasi
202
37
0
01 Oct 2018
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep
  Convolutional Networks
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks
Kenneth T. Co
Luis Muñoz-González
Sixte de Maupeou
Emil C. Lupu
AAML
424
73
0
30 Sep 2018
To compress or not to compress: Understanding the Interactions between
  Adversarial Attacks and Neural Network Compression
To compress or not to compress: Understanding the Interactions between Adversarial Attacks and Neural Network Compression
Yiren Zhao
Ilia Shumailov
Robert D. Mullins
Ross J. Anderson
AAML
209
44
0
29 Sep 2018
Adversarial Attacks and Defences: A Survey
Adversarial Attacks and Defences: A Survey
Anirban Chakraborty
Manaar Alam
Vishal Dey
Anupam Chattopadhyay
Debdeep Mukhopadhyay
AAMLOOD
391
722
0
28 Sep 2018
Scenic: A Language for Scenario Specification and Scene Generation
Scenic: A Language for Scenario Specification and Scene GenerationACM-SIGPLAN Symposium on Programming Language Design and Implementation (PLDI), 2018
Daniel J. Fremont
T. Dreossi
Shromona Ghosh
Xiangyu Yue
Alberto L. Sangiovanni-Vincentelli
Sanjit A. Seshia
254
293
0
25 Sep 2018
Fast Geometrically-Perturbed Adversarial Faces
Fast Geometrically-Perturbed Adversarial FacesIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2018
Ali Dabouei
Sobhan Soleymani
J. Dawson
Nasser M. Nasrabadi
CVBMAAML
191
70
0
24 Sep 2018
On The Utility of Conditional Generation Based Mutual Information for
  Characterizing Adversarial Subspaces
On The Utility of Conditional Generation Based Mutual Information for Characterizing Adversarial SubspacesIEEE Global Conference on Signal and Information Processing (GlobalSIP), 2018
Chia-Yi Hsu
Pei-Hsuan Lu
Pin-Yu Chen
Chia-Mu Yu
AAML
192
1
0
24 Sep 2018
Low Frequency Adversarial Perturbation
Low Frequency Adversarial PerturbationConference on Uncertainty in Artificial Intelligence (UAI), 2018
Chuan Guo
Jared S. Frank
Kilian Q. Weinberger
AAML
248
187
0
24 Sep 2018
Adversarial Recommendation: Attack of the Learned Fake Users
Adversarial Recommendation: Attack of the Learned Fake Users
Konstantina Christakopoulou
A. Banerjee
AAML
112
13
0
21 Sep 2018
Playing the Game of Universal Adversarial Perturbations
Playing the Game of Universal Adversarial Perturbations
Julien Perolat
Mateusz Malinowski
Bilal Piot
Olivier Pietquin
AAML
134
26
0
20 Sep 2018
Generating 3D Adversarial Point Clouds
Generating 3D Adversarial Point Clouds
Chong Xiang
C. Qi
Yue Liu
3DPC
247
351
0
19 Sep 2018
Model-Protected Multi-Task Learning
Model-Protected Multi-Task Learning
Jian Liang
Ziqi Liu
Jiayu Zhou
Xiaoqian Jiang
Changshui Zhang
Fei Wang
211
13
0
18 Sep 2018
Exploring the Vulnerability of Single Shot Module in Object Detectors
  via Imperceptible Background Patches
Exploring the Vulnerability of Single Shot Module in Object Detectors via Imperceptible Background Patches
Yuezun Li
Xiao Bian
Ming-Ching Chang
Siwei Lyu
AAMLObjD
226
33
0
16 Sep 2018
Robust Adversarial Perturbation on Deep Proposal-based Models
Robust Adversarial Perturbation on Deep Proposal-based Models
Yuezun Li
Dan Tian
Ming-Ching Chang
Xiao Bian
Siwei Lyu
AAML
192
118
0
16 Sep 2018
Query-Efficient Black-Box Attack by Active Learning
Query-Efficient Black-Box Attack by Active Learning
Pengcheng Li
Jinfeng Yi
Lijun Zhang
AAMLMLAU
133
58
0
13 Sep 2018
Adversarial Examples: Opportunities and Challenges
Adversarial Examples: Opportunities and Challenges
Jiliang Zhang
Chen Li
AAML
241
270
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
195
66
0
11 Sep 2018
Certified Adversarial Robustness with Additive Noise
Certified Adversarial Robustness with Additive Noise
Bai Li
Changyou Chen
Wenlin Wang
Lawrence Carin
AAML
444
371
0
10 Sep 2018
Towards Query Efficient Black-box Attacks: An Input-free Perspective
Towards Query Efficient Black-box Attacks: An Input-free Perspective
Yali Du
Meng Fang
Jinfeng Yi
Jun Cheng
Dacheng Tao
AAML
145
21
0
09 Sep 2018
Query Attack via Opposite-Direction Feature:Towards Robust Image
  Retrieval
Query Attack via Opposite-Direction Feature:Towards Robust Image Retrieval
Zhedong Zheng
Liang Zheng
Yi Yang
Zhilan Hu
AAML
203
25
0
07 Sep 2018
Bridging machine learning and cryptography in defence against
  adversarial attacks
Bridging machine learning and cryptography in defence against adversarial attacks
O. Taran
Shideh Rezaeifar
Svyatoslav Voloshynovskiy
AAML
129
24
0
05 Sep 2018
Adversarial Attack Type I: Cheat Classifiers by Significant Changes
Adversarial Attack Type I: Cheat Classifiers by Significant Changes
Sanli Tang
Xiaolin Huang
Mingjian Chen
Chengjin Sun
J. Yang
AAML
181
2
0
03 Sep 2018
MULDEF: Multi-model-based Defense Against Adversarial Examples for
  Neural Networks
MULDEF: Multi-model-based Defense Against Adversarial Examples for Neural Networks
Siwakorn Srisakaokul
Yuhao Zhang
Zexuan Zhong
Wei Yang
Tao Xie
Bo Li
AAML
215
20
0
31 Aug 2018
Backdoor Embedding in Convolutional Neural Network Models via Invisible
  Perturbation
Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation
C. Liao
Haoti Zhong
Anna Squicciarini
Sencun Zhu
David J. Miller
SILM
183
341
0
30 Aug 2018
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