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Obfuscated Gradients Give a False Sense of Security: Circumventing
  Defenses to Adversarial Examples
v1v2v3v4 (latest)

Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

1 February 2018
Anish Athalye
Nicholas Carlini
D. Wagner
    AAML
ArXiv (abs)PDFHTML

Papers citing "Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples"

50 / 1,983 papers shown
Adversarial Contrastive Learning via Asymmetric InfoNCE
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Xianyuan Zhan
Qizhang Li
W. Zuo
Yang Liu
Jingjing Liu
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187
30
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Automated Repair of Neural Networks
Automated Repair of Neural Networks
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O. Strichman
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87
4
0
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Achieve Optimal Adversarial Accuracy for Adversarial Deep Learning using
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Xiao-Shan Gao
Shuang Liu
Lijia Yu
AAML
238
1
0
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Threat Model-Agnostic Adversarial Defense using Diffusion Models
Threat Model-Agnostic Adversarial Defense using Diffusion Models
Tsachi Blau
Roy Ganz
Bahjat Kawar
Alex M. Bronstein
Michael Elad
AAMLDiffM
223
35
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3DVerifier: Efficient Robustness Verification for 3D Point Cloud Models
3DVerifier: Efficient Robustness Verification for 3D Point Cloud ModelsMachine-mediated learning (ML), 2022
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Wenjie Ruan
Leandro Soriano Marcolino
Q. Ni
3DPC
239
12
0
15 Jul 2022
Sound Randomized Smoothing in Floating-Point Arithmetics
Sound Randomized Smoothing in Floating-Point ArithmeticsInternational Conference on Learning Representations (ICLR), 2022
Václav Voráček
Matthias Hein
272
5
0
14 Jul 2022
Provably Adversarially Robust Nearest Prototype Classifiers
Provably Adversarially Robust Nearest Prototype ClassifiersInternational Conference on Machine Learning (ICML), 2022
Václav Voráček
Matthias Hein
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227
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14 Jul 2022
On the Robustness of Bayesian Neural Networks to Adversarial Attacks
On the Robustness of Bayesian Neural Networks to Adversarial AttacksIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Luca Bortolussi
Ginevra Carbone
Luca Laurenti
A. Patané
G. Sanguinetti
Matthew Wicker
AAML
270
14
0
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Perturbation Inactivation Based Adversarial Defense for Face Recognition
Perturbation Inactivation Based Adversarial Defense for Face RecognitionIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2022
Min Ren
Yuhao Zhu
Yunlong Wang
Zhenan Sun
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207
21
0
13 Jul 2022
Adversarial Robustness Assessment of NeuroEvolution Approaches
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Nuno Lourenço
Nuno Antunes
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147
1
0
12 Jul 2022
Certified Adversarial Robustness via Anisotropic Randomized Smoothing
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Hanbin Hong
Yuan Hong
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241
6
0
12 Jul 2022
Towards Effective Multi-Label Recognition Attacks via Knowledge Graph
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Hassan Mahmood
Ehsan Elhamifar
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134
0
0
11 Jul 2022
RUSH: Robust Contrastive Learning via Randomized Smoothing
Yijiang Pang
Boyang Liu
Jiayu Zhou
OODAAML
172
1
0
11 Jul 2022
Dynamic Time Warping based Adversarial Framework for Time-Series Domain
Dynamic Time Warping based Adversarial Framework for Time-Series DomainIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Taha Belkhouja
Yan Yan
J. Doppa
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159
42
0
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Adversarial Framework with Certified Robustness for Time-Series Domain
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Adversarial Framework with Certified Robustness for Time-Series Domain via Statistical FeaturesJournal of Artificial Intelligence Research (JAIR), 2022
Taha Belkhouja
J. Doppa
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162
16
0
09 Jul 2022
Jacobian Norm with Selective Input Gradient Regularization for Improved
  and Interpretable Adversarial Defense
Jacobian Norm with Selective Input Gradient Regularization for Improved and Interpretable Adversarial Defense
Deyin Liu
Lin Wu
Haifeng Zhao
F. Boussaïd
Bennamoun
Xianghua Xie
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315
3
0
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How many perturbations break this model? Evaluating robustness beyond
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How many perturbations break this model? Evaluating robustness beyond adversarial accuracyInternational Conference on Machine Learning (ICML), 2022
R. Olivier
Bhiksha Raj
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204
9
0
08 Jul 2022
PatchZero: Defending against Adversarial Patch Attacks by Detecting and
  Zeroing the Patch
PatchZero: Defending against Adversarial Patch Attacks by Detecting and Zeroing the PatchIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2022
Ke Xu
Yao Xiao
Zhao-Heng Zheng
Kaijie Cai
Ramkant Nevatia
AAML
285
50
0
05 Jul 2022
Hessian-Free Second-Order Adversarial Examples for Adversarial Learning
Hessian-Free Second-Order Adversarial Examples for Adversarial Learning
Yaguan Qian
Yu-qun Wang
Bin Wang
Zhaoquan Gu
Yu-Shuang Guo
Wassim Swaileh
AAML
242
4
0
04 Jul 2022
Threat Assessment in Machine Learning based Systems
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L. Tidjon
Foutse Khomh
156
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MEAD: A Multi-Armed Approach for Evaluation of Adversarial Examples
  Detectors
MEAD: A Multi-Armed Approach for Evaluation of Adversarial Examples Detectors
Federica Granese
Marine Picot
Marco Romanelli
Francisco Messina
Pablo Piantanida
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185
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30 Jun 2022
Increasing Confidence in Adversarial Robustness Evaluations
Increasing Confidence in Adversarial Robustness EvaluationsNeural Information Processing Systems (NeurIPS), 2022
Roland S. Zimmermann
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Florian Tramèr
Nicholas Carlini
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195
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Self-Healing Robust Neural Networks via Closed-Loop Control
Self-Healing Robust Neural Networks via Closed-Loop ControlJournal of machine learning research (JMLR), 2022
Zhuotong Chen
Qianxiao Li
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124
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Adversarial Self-Attention for Language Understanding
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Hongqiu Wu
Ruixue Ding
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Fei Huang
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285
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25 Jun 2022
AdAUC: End-to-end Adversarial AUC Optimization Against Long-tail
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AdAUC: End-to-end Adversarial AUC Optimization Against Long-tail ProblemsInternational Conference on Machine Learning (ICML), 2022
Wen-ming Hou
Qianqian Xu
Zhiyong Yang
Shilong Bao
Yuan He
Qingming Huang
AAML
196
6
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24 Jun 2022
InfoAT: Improving Adversarial Training Using the Information Bottleneck
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InfoAT: Improving Adversarial Training Using the Information Bottleneck PrincipleIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Mengting Xu
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Zhongnian Li
Daoqiang Zhang
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158
20
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23 Jun 2022
(Certified!!) Adversarial Robustness for Free!
(Certified!!) Adversarial Robustness for Free!International Conference on Learning Representations (ICLR), 2022
Nicholas Carlini
Florian Tramèr
Krishnamurthy Dvijotham
Leslie Rice
Mingjie Sun
J. Zico Kolter
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492
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21 Jun 2022
On the Limitations of Stochastic Pre-processing Defenses
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Yue Gao
Ilia Shumailov
Kassem Fawaz
Nicolas Papernot
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371
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A Universal Adversarial Policy for Text Classifiers
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Gallil Maimon
Lior Rokach
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240
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Low-Mid Adversarial Perturbation against Unauthorized Face Recognition
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Low-Mid Adversarial Perturbation against Unauthorized Face Recognition SystemInformation Sciences (Inf. Sci.), 2022
Jiaming Zhang
Qiaomin Yi
Dongyuan Lu
Jitao Sang
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157
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19 Jun 2022
Demystifying the Adversarial Robustness of Random Transformation
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Demystifying the Adversarial Robustness of Random Transformation DefensesInternational Conference on Machine Learning (ICML), 2022
Chawin Sitawarin
Zachary Golan-Strieb
David Wagner
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275
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Landscape Learning for Neural Network Inversion
Landscape Learning for Neural Network InversionIEEE International Conference on Computer Vision (ICCV), 2022
Ruoshi Liu
Chen-Guang Mao
Purva Tendulkar
Hongya Wang
Carl Vondrick
219
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RetrievalGuard: Provably Robust 1-Nearest Neighbor Image Retrieval
RetrievalGuard: Provably Robust 1-Nearest Neighbor Image RetrievalInternational Conference on Machine Learning (ICML), 2022
Yihan Wu
Hongyang R. Zhang
Heng Huang
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177
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Understanding Robust Overfitting of Adversarial Training and Beyond
Understanding Robust Overfitting of Adversarial Training and BeyondInternational Conference on Machine Learning (ICML), 2022
Chaojian Yu
Bo Han
Li Shen
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Chen Gong
Biwei Huang
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234
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Analysis and Extensions of Adversarial Training for Video Classification
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229
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Double Sampling Randomized Smoothing
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513
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Hardening DNNs against Transfer Attacks during Network Compression using
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Tiago A. O. Alves
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Efficiently Training Low-Curvature Neural Networks
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222
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Adversarial Vulnerability of Randomized Ensembles
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Erik G. Larsson
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Towards Alternative Techniques for Improving Adversarial Robustness:
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James Weimer
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150
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Distributed Adversarial Training to Robustify Deep Neural Networks at
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Gaoyuan Zhang
Songtao Lu
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Xiangyi Chen
Pin-Yu Chen
Quanfu Fan
Lee Martie
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Min-Fong Hong
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Pixel to Binary Embedding Towards Robustness for CNNs
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Ikki Kishida
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253
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NeuGuard: Lightweight Neuron-Guided Defense against Membership Inference
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241
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ReFace: Real-time Adversarial Attacks on Face Recognition Systems
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Chris Mesterharm
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