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Towards Deep Learning Models Resistant to Adversarial Attacks
v1v2v3v4 (latest)

Towards Deep Learning Models Resistant to Adversarial Attacks

19 June 2017
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
    SILMOOD
ArXiv (abs)PDFHTMLGithub (752★)

Papers citing "Towards Deep Learning Models Resistant to Adversarial Attacks"

50 / 7,066 papers shown
Persistency of Excitation for Robustness of Neural Networks
Persistency of Excitation for Robustness of Neural Networks
Kamil Nar
S. Shankar Sastry
AAML
109
13
0
04 Nov 2019
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional
  Networks
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional NetworksNeural Information Processing Systems (NeurIPS), 2019
Qiyang Li
Saminul Haque
Cem Anil
James Lucas
Roger C. Grosse
Joern-Henrik Jacobsen
397
119
0
03 Nov 2019
Who is Real Bob? Adversarial Attacks on Speaker Recognition Systems
Who is Real Bob? Adversarial Attacks on Speaker Recognition SystemsIEEE Symposium on Security and Privacy (IEEE S&P), 2019
Guangke Chen
Sen Chen
Lingling Fan
Xiaoning Du
Zhe Zhao
Fu Song
Yang Liu
AAML
262
225
0
03 Nov 2019
Online Robustness Training for Deep Reinforcement Learning
Online Robustness Training for Deep Reinforcement Learning
Marc Fischer
M. Mirman
Steven Stalder
Martin Vechev
OnRL
326
49
0
03 Nov 2019
MadNet: Using a MAD Optimization for Defending Against Adversarial
  Attacks
MadNet: Using a MAD Optimization for Defending Against Adversarial Attacks
Shai Rozenberg
G. Elidan
Ran El-Yaniv
AAML
120
1
0
03 Nov 2019
Adversarial Music: Real World Audio Adversary Against Wake-word
  Detection System
Adversarial Music: Real World Audio Adversary Against Wake-word Detection SystemNeural Information Processing Systems (NeurIPS), 2019
Juncheng Billy Li
Shuhui Qu
Xinjian Li
Joseph Szurley
J. Zico Kolter
Florian Metze
AAML
315
71
0
31 Oct 2019
Making an Invisibility Cloak: Real World Adversarial Attacks on Object
  Detectors
Making an Invisibility Cloak: Real World Adversarial Attacks on Object DetectorsEuropean Conference on Computer Vision (ECCV), 2019
Zuxuan Wu
Ser-Nam Lim
L. Davis
Tom Goldstein
AAML
349
304
0
31 Oct 2019
Enhancing Certifiable Robustness via a Deep Model Ensemble
Enhancing Certifiable Robustness via a Deep Model Ensemble
Huan Zhang
Minhao Cheng
Cho-Jui Hsieh
130
9
0
31 Oct 2019
A Decentralized Proximal Point-type Method for Saddle Point Problems
A Decentralized Proximal Point-type Method for Saddle Point Problems
Weijie Liu
Aryan Mokhtari
Asuman Ozdaglar
S. Pattathil
Zebang Shen
Nenggan Zheng
289
33
0
31 Oct 2019
Investigating Resistance of Deep Learning-based IDS against Adversaries
  using min-max Optimization
Investigating Resistance of Deep Learning-based IDS against Adversaries using min-max Optimization
Rana Abou-Khamis
Omair Shafiq
Ashraf Matrawy
AAML
166
48
0
30 Oct 2019
Fault Tolerance of Neural Networks in Adversarial Settings
Fault Tolerance of Neural Networks in Adversarial SettingsJournal of Intelligent & Fuzzy Systems (JIFS), 2019
Vasisht Duddu
N. Pillai
D. V. Rao
V. Balas
SILMAAML
186
12
0
30 Oct 2019
Efficiently avoiding saddle points with zero order methods: No gradients
  required
Efficiently avoiding saddle points with zero order methods: No gradients requiredNeural Information Processing Systems (NeurIPS), 2019
Lampros Flokas
Emmanouil-Vasileios Vlatakis-Gkaragkounis
Georgios Piliouras
146
35
0
29 Oct 2019
Certified Adversarial Robustness for Deep Reinforcement Learning
Certified Adversarial Robustness for Deep Reinforcement LearningConference on Robot Learning (CoRL), 2019
Björn Lütjens
Michael Everett
Jonathan P. How
AAML
194
102
0
28 Oct 2019
Dr.VOT : Measuring Positive and Negative Voice Onset Time in the Wild
Dr.VOT : Measuring Positive and Negative Voice Onset Time in the WildInterspeech (Interspeech), 2019
Yosi Shrem
Matthew A. Goldrick
Joseph Keshet
62
13
0
27 Oct 2019
Adversarial Defense via Local Flatness Regularization
Adversarial Defense via Local Flatness RegularizationInternational Conference on Information Photonics (ICIP), 2019
Jia Xu
Yiming Li
Yong Jiang
Shutao Xia
AAML
244
21
0
27 Oct 2019
Understanding and Quantifying Adversarial Examples Existence in Linear
  Classification
Understanding and Quantifying Adversarial Examples Existence in Linear ClassificationInternational Conference on Machine Learning and Computing (ICMLC), 2019
Xupeng Shi
A. Ding
AAML
85
3
0
27 Oct 2019
Effectiveness of random deep feature selection for securing image
  manipulation detectors against adversarial examples
Effectiveness of random deep feature selection for securing image manipulation detectors against adversarial examplesIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019
Mauro Barni
Ehsan Nowroozi
B. Tondi
Bowen Zhang
AAML
194
17
0
25 Oct 2019
A Simple Dynamic Learning Rate Tuning Algorithm For Automated Training
  of DNNs
A Simple Dynamic Learning Rate Tuning Algorithm For Automated Training of DNNs
Koyel Mukherjee
Alind Khare
Ashish Verma
143
20
0
25 Oct 2019
Label Smoothing and Logit Squeezing: A Replacement for Adversarial
  Training?
Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training?
Ali Shafahi
Amin Ghiasi
Furong Huang
Tom Goldstein
AAML
132
43
0
25 Oct 2019
ATZSL: Defensive Zero-Shot Recognition in the Presence of Adversaries
ATZSL: Defensive Zero-Shot Recognition in the Presence of AdversariesIEEE transactions on multimedia (IEEE TMM), 2019
Xingxing Zhang
Shupeng Gui
Zhenfeng Zhu
Yao Zhao
Ji Liu
VLM
151
10
0
24 Oct 2019
Diametrical Risk Minimization: Theory and Computations
Diametrical Risk Minimization: Theory and ComputationsMachine-mediated learning (ML), 2019
Matthew Norton
Pratiksha Agrawal
270
20
0
24 Oct 2019
Wasserstein Smoothing: Certified Robustness against Wasserstein
  Adversarial Attacks
Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial AttacksInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Alexander Levine
Soheil Feizi
AAML
149
63
0
23 Oct 2019
A Useful Taxonomy for Adversarial Robustness of Neural Networks
A Useful Taxonomy for Adversarial Robustness of Neural NetworksTrends in Computer Science and Information Technology (TCSIT), 2019
L. Smith
AAML
131
6
0
23 Oct 2019
Structure Matters: Towards Generating Transferable Adversarial Images
Structure Matters: Towards Generating Transferable Adversarial ImagesEuropean Conference on Artificial Intelligence (ECAI), 2019
Dan Peng
Zizhan Zheng
Linhao Luo
Xiaofeng Zhang
AAML
194
2
0
22 Oct 2019
An Alternative Surrogate Loss for PGD-based Adversarial Testing
An Alternative Surrogate Loss for PGD-based Adversarial Testing
Sven Gowal
J. Uesato
Chongli Qin
Po-Sen Huang
Timothy A. Mann
Pushmeet Kohli
AAML
272
92
0
21 Oct 2019
Improving Sequence Modeling Ability of Recurrent Neural Networks via
  Sememes
Improving Sequence Modeling Ability of Recurrent Neural Networks via Sememes
Yujia Qin
Fanchao Qi
Sicong Ouyang
Zhiyuan Liu
Cheng Yang
Yasheng Wang
Qun Liu
Maosong Sun
166
5
0
20 Oct 2019
Adversarial Attacks on Spoofing Countermeasures of automatic speaker
  verification
Adversarial Attacks on Spoofing Countermeasures of automatic speaker verificationAutomatic Speech Recognition & Understanding (ASRU), 2019
Songxiang Liu
Haibin Wu
Hung-yi Lee
Helen Meng
AAML
134
68
0
19 Oct 2019
Are Perceptually-Aligned Gradients a General Property of Robust
  Classifiers?
Are Perceptually-Aligned Gradients a General Property of Robust Classifiers?
Simran Kaur
Jeremy M. Cohen
Zachary Chase Lipton
OODAAML
224
68
0
18 Oct 2019
A Fast Saddle-Point Dynamical System Approach to Robust Deep Learning
A Fast Saddle-Point Dynamical System Approach to Robust Deep Learning
Yasaman Esfandiari
Aditya Balu
K. Ebrahimi
Umesh Vaidya
N. Elia
Soumik Sarkar
OOD
181
3
0
18 Oct 2019
Enforcing Linearity in DNN succours Robustness and Adversarial Image
  Generation
Enforcing Linearity in DNN succours Robustness and Adversarial Image GenerationInternational Conference on Artificial Neural Networks (ICANN), 2019
A. Sarkar
Nikhil Kumar Gupta
Raghu Sesha Iyengar
AAML
126
11
0
17 Oct 2019
Instance adaptive adversarial training: Improved accuracy tradeoffs in
  neural nets
Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets
Yogesh Balaji
Tom Goldstein
Judy Hoffman
AAML
311
111
0
17 Oct 2019
A New Defense Against Adversarial Images: Turning a Weakness into a
  Strength
A New Defense Against Adversarial Images: Turning a Weakness into a StrengthNeural Information Processing Systems (NeurIPS), 2019
Tao Yu
Shengyuan Hu
Chuan Guo
Wei-Lun Chao
Kilian Q. Weinberger
AAML
223
111
0
16 Oct 2019
MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural
  Network Design
MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design
Mayoore S. Jaiswal
Bumboo Kang
Jinho Lee
Minsik Cho
109
2
0
15 Oct 2019
Extracting robust and accurate features via a robust information
  bottleneck
Extracting robust and accurate features via a robust information bottleneckIEEE Journal on Selected Areas in Information Theory (JSAIT), 2019
Ankit Pensia
Varun Jog
Po-Ling Loh
AAML
139
23
0
15 Oct 2019
ODE guided Neural Data Augmentation Techniques for Time Series Data and
  its Benefits on Robustness
ODE guided Neural Data Augmentation Techniques for Time Series Data and its Benefits on Robustness
A. Sarkar
A. Raj
Raghu Sesha Iyengar
AAMLAI4TS
195
0
0
15 Oct 2019
Understanding Misclassifications by Attributes
Understanding Misclassifications by Attributes
Sadaf Gulshad
Zeynep Akata
J. H. Metzen
A. Smeulders
AAML
153
0
0
15 Oct 2019
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box
  Optimization
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box OptimizationNeural Information Processing Systems (NeurIPS), 2019
Xiangyi Chen
Sijia Liu
Kaidi Xu
Xingguo Li
Xue Lin
Mingyi Hong
David Cox
ODL
192
133
0
15 Oct 2019
DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural
  Networks
DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural Networks
Fuyuan Zhang
Sankalan Pal Chowdhury
M. Christakis
AAML
175
8
0
14 Oct 2019
Confidence-Calibrated Adversarial Training: Generalizing to Unseen
  Attacks
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks
David Stutz
Matthias Hein
Bernt Schiele
AAML
333
5
0
14 Oct 2019
Man-in-the-Middle Attacks against Machine Learning Classifiers via
  Malicious Generative Models
Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative ModelsIEEE Transactions on Dependable and Secure Computing (TDSC), 2019
Derui Wang
Wang
Chaoran Li
S. Wen
Surya Nepal
Yang Xiang
AAML
126
40
0
14 Oct 2019
On Robustness of Neural Ordinary Differential Equations
On Robustness of Neural Ordinary Differential EquationsInternational Conference on Learning Representations (ICLR), 2019
Hanshu Yan
Jiawei Du
Vincent Y. F. Tan
Jiashi Feng
OOD
321
154
0
12 Oct 2019
Hear "No Evil", See "Kenansville": Efficient and Transferable Black-Box
  Attacks on Speech Recognition and Voice Identification Systems
Hear "No Evil", See "Kenansville": Efficient and Transferable Black-Box Attacks on Speech Recognition and Voice Identification Systems
H. Abdullah
Muhammad Sajidur Rahman
Washington Garcia
Logan Blue
Kevin Warren
Anurag Swarnim Yadav
T. Shrimpton
Patrick Traynor
AAML
141
95
0
11 Oct 2019
Noise as a Resource for Learning in Knowledge Distillation
Noise as a Resource for Learning in Knowledge Distillation
Elahe Arani
F. Sarfraz
Bahram Zonooz
180
6
0
11 Oct 2019
Verification of Neural Networks: Specifying Global Robustness using
  Generative Models
Verification of Neural Networks: Specifying Global Robustness using Generative Models
Nathanaël Fijalkow
M. Gupta
AAML
65
3
0
11 Oct 2019
Information Aware Max-Norm Dirichlet Networks for Predictive Uncertainty
  Estimation
Information Aware Max-Norm Dirichlet Networks for Predictive Uncertainty Estimation
Theodoros Tsiligkaridis
UQCVBDL
205
9
0
10 Oct 2019
Improved Sample Complexities for Deep Networks and Robust Classification
  via an All-Layer Margin
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer MarginInternational Conference on Learning Representations (ICLR), 2019
Colin Wei
Tengyu Ma
AAMLOOD
521
88
0
09 Oct 2019
Deep Latent Defence
Deep Latent Defence
Giulio Zizzo
C. Hankin
S. Maffeis
K. Jones
AAML
160
2
0
09 Oct 2019
Adversarial Learning of Deepfakes in Accounting
Adversarial Learning of Deepfakes in Accounting
Marco Schreyer
Timur Sattarov
Bernd Reimer
Damian Borth
AAML
155
26
0
09 Oct 2019
SmoothFool: An Efficient Framework for Computing Smooth Adversarial
  Perturbations
SmoothFool: An Efficient Framework for Computing Smooth Adversarial PerturbationsIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2019
Ali Dabouei
Sobhan Soleymani
Fariborz Taherkhani
J. Dawson
Nasser M. Nasrabadi
AAML
233
22
0
08 Oct 2019
Directional Adversarial Training for Cost Sensitive Deep Learning
  Classification Applications
Directional Adversarial Training for Cost Sensitive Deep Learning Classification ApplicationsEngineering applications of artificial intelligence (EAAI), 2019
M. Terzi
Gian Antonio Susto
Pratik Chaudhari
OODAAML
127
17
0
08 Oct 2019
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