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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
A Closer Look at Evaluating the Bit-Flip Attack Against Deep Neural
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A Closer Look at Evaluating the Bit-Flip Attack Against Deep Neural NetworksIEEE International Symposium on On-Line Testing and Robust System Design (IOLTS), 2022
Kevin Hector
Mathieu Dumont
Pierre-Alain Moëllic
J. Dutertre
AAML
171
6
0
28 Sep 2022
The "Beatrix'' Resurrections: Robust Backdoor Detection via Gram
  Matrices
The "Beatrix'' Resurrections: Robust Backdoor Detection via Gram MatricesNetwork and Distributed System Security Symposium (NDSS), 2022
Wanlun Ma
Derui Wang
Ruoxi Sun
Minhui Xue
S. Wen
Yang Xiang
AAML
320
107
0
23 Sep 2022
Fair Robust Active Learning by Joint Inconsistency
Fair Robust Active Learning by Joint Inconsistency
Tsung-Han Wu
Hung-Ting Su
Shang-Tse Chen
Winston H. Hsu
AAML
206
2
0
22 Sep 2022
Watch What You Pretrain For: Targeted, Transferable Adversarial Examples
  on Self-Supervised Speech Recognition models
Watch What You Pretrain For: Targeted, Transferable Adversarial Examples on Self-Supervised Speech Recognition models
R. Olivier
H. Abdullah
Bhiksha Raj
AAML
272
1
0
17 Sep 2022
Towards Bridging the Performance Gaps of Joint Energy-based Models
Towards Bridging the Performance Gaps of Joint Energy-based ModelsComputer Vision and Pattern Recognition (CVPR), 2022
Xiulong Yang
Qing Su
Shihao Ji
VLM
301
18
0
16 Sep 2022
Explicit Tradeoffs between Adversarial and Natural Distributional
  Robustness
Explicit Tradeoffs between Adversarial and Natural Distributional RobustnessNeural Information Processing Systems (NeurIPS), 2022
Mazda Moayeri
Kiarash Banihashem
Soheil Feizi
OOD
297
26
0
15 Sep 2022
Part-Based Models Improve Adversarial Robustness
Part-Based Models Improve Adversarial RobustnessInternational Conference on Learning Representations (ICLR), 2022
Chawin Sitawarin
Kornrapat Pongmala
Yizheng Chen
Nicholas Carlini
David Wagner
271
14
0
15 Sep 2022
Robustness in deep learning: The good (width), the bad (depth), and the
  ugly (initialization)
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization)Neural Information Processing Systems (NeurIPS), 2022
Zhenyu Zhu
Fanghui Liu
Grigorios G. Chrysos
Volkan Cevher
361
23
0
15 Sep 2022
PointACL:Adversarial Contrastive Learning for Robust Point Clouds
  Representation under Adversarial Attack
PointACL:Adversarial Contrastive Learning for Robust Point Clouds Representation under Adversarial Attack
Junxuan Huang
Yatong An
Lu Cheng
Bai Chen
Junsong Yuan
Chunming Qiao
3DPC
177
3
0
14 Sep 2022
Robust Transferable Feature Extractors: Learning to Defend Pre-Trained
  Networks Against White Box Adversaries
Robust Transferable Feature Extractors: Learning to Defend Pre-Trained Networks Against White Box Adversaries
Alexander Cann
Ian Colbert
I. Amer
AAML
140
1
0
14 Sep 2022
TSFool: Crafting Highly-Imperceptible Adversarial Time Series through
  Multi-Objective Attack
TSFool: Crafting Highly-Imperceptible Adversarial Time Series through Multi-Objective AttackEuropean Conference on Artificial Intelligence (ECAI), 2022
Yanyun Wang
Dehui Du
Haibo Hu
Zi Liang
Yuanhao Liu
AAMLAI4TS
286
9
0
14 Sep 2022
CARE: Certifiably Robust Learning with Reasoning via Variational
  Inference
CARE: Certifiably Robust Learning with Reasoning via Variational Inference
Jiawei Zhang
Linyi Li
Ce Zhang
Yue Liu
AAMLOOD
393
12
0
12 Sep 2022
The Space of Adversarial Strategies
The Space of Adversarial Strategies
Ryan Sheatsley
Blaine Hoak
Eric Pauley
Patrick McDaniel
AAML
231
6
0
09 Sep 2022
Defending Against Backdoor Attack on Graph Nerual Network by
  Explainability
Defending Against Backdoor Attack on Graph Nerual Network by Explainability
B. Jiang
Zhao Li
AAMLGNN
245
23
0
07 Sep 2022
Attacking the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples
Attacking the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial ExamplesNeurocomputing (Neurocomputing), 2022
Nuo Xu
Kaleel Mahmood
Haowen Fang
Ethan Rathbun
Caiwen Ding
Wujie Wen
AAML
444
15
0
07 Sep 2022
Revisiting Outer Optimization in Adversarial Training
Revisiting Outer Optimization in Adversarial TrainingEuropean Conference on Computer Vision (ECCV), 2022
Ali Dabouei
Fariborz Taherkhani
Sobhan Soleymani
Nasser M. Nasrabadi
AAML
257
6
0
02 Sep 2022
Be Your Own Neighborhood: Detecting Adversarial Example by the
  Neighborhood Relations Built on Self-Supervised Learning
Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised LearningInternational Conference on Machine Learning (ICML), 2022
Zhiyuan He
Yijun Yang
Pin-Yu Chen
Qiang Xu
Tsung-Yi Ho
AAML
241
9
0
31 Aug 2022
Unrestricted Adversarial Samples Based on Non-semantic Feature Clusters
  Substitution
Unrestricted Adversarial Samples Based on Non-semantic Feature Clusters Substitution
Ming-Kuai Zhou
Xiaobing Pei
AAML
158
0
0
31 Aug 2022
Towards Adversarial Purification using Denoising AutoEncoders
Towards Adversarial Purification using Denoising AutoEncoders
Dvij Kalaria
Aritra Hazra
P. Chakrabarti
DiffM
142
8
0
29 Aug 2022
SA: Sliding attack for synthetic speech detection with resistance to clipping and self-splicing
JiaCheng Deng
Dong Li
Yan Diqun
Rangding Wang
Zeng Jiaming
AAML
97
0
0
27 Aug 2022
A Perturbation Resistant Transformation and Classification System for
  Deep Neural Networks
A Perturbation Resistant Transformation and Classification System for Deep Neural Networks
Nathaniel R. Dean
D. Sarkar
AAML
108
0
0
25 Aug 2022
Black-box Attacks Against Neural Binary Function Detection
Black-box Attacks Against Neural Binary Function DetectionInternational Symposium on Recent Advances in Intrusion Detection (RAID), 2022
Josh Bundt
Michael Davinroy
Ioannis Agadakos
Alina Oprea
William K. Robertson
AAML
198
2
0
24 Aug 2022
Unrestricted Black-box Adversarial Attack Using GAN with Limited Queries
Unrestricted Black-box Adversarial Attack Using GAN with Limited Queries
Dongbin Na
Sangwoo Ji
Jong Kim
AAML
233
27
0
24 Aug 2022
Auditing Membership Leakages of Multi-Exit Networks
Auditing Membership Leakages of Multi-Exit NetworksConference on Computer and Communications Security (CCS), 2022
Zheng Li
Yiyong Liu
Xinlei He
Ning Yu
Michael Backes
Yang Zhang
AAML
195
46
0
23 Aug 2022
Adversarial Vulnerability of Temporal Feature Networks for Object
  Detection
Adversarial Vulnerability of Temporal Feature Networks for Object Detection
Svetlana Pavlitskaya
Nikolai Polley
Michael Weber
J. Marius Zöllner
AAML
192
7
0
23 Aug 2022
PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D
  Point Cloud Recognition
PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition
Jiachen Sun
Weili Nie
Zhiding Yu
Z. Morley Mao
Chaowei Xiao
DiffM
146
28
0
21 Aug 2022
Resisting Adversarial Attacks in Deep Neural Networks using Diverse
  Decision Boundaries
Resisting Adversarial Attacks in Deep Neural Networks using Diverse Decision Boundaries
Manaar Alam
Shubhajit Datta
Debdeep Mukhopadhyay
Arijit Mondal
P. Chakrabarti
AAML
132
5
0
18 Aug 2022
An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for
  Generating Adversarial Instances in Deep Networks
An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Networks
Raz Lapid
Zvika Haramaty
Moshe Sipper
AAMLMLAU
199
14
0
17 Aug 2022
On the Privacy Effect of Data Enhancement via the Lens of Memorization
On the Privacy Effect of Data Enhancement via the Lens of MemorizationIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2022
Xiao-Li Li
Qiongxiu Li
Zhan Hu
Xiaolin Hu
294
20
0
17 Aug 2022
Two Heads are Better than One: Robust Learning Meets Multi-branch Models
Two Heads are Better than One: Robust Learning Meets Multi-branch Models
Dong Huang
Qi Bu
Yuhao Qing
Haowen Pi
Sen Wang
Zihan Fang
Heming Cui
Dong Huang
OODAAML
348
2
0
17 Aug 2022
An Overview and Prospective Outlook on Robust Training and Certification
  of Machine Learning Models
An Overview and Prospective Outlook on Robust Training and Certification of Machine Learning Models
Brendon G. Anderson
Tanmay Gautam
Somayeh Sojoudi
OOD
264
2
0
15 Aug 2022
Unifying Gradients to Improve Real-world Robustness for Deep Networks
Unifying Gradients to Improve Real-world Robustness for Deep NetworksACM Transactions on Intelligent Systems and Technology (ACM TIST), 2022
Yingwen Wu
Sizhe Chen
Kun Fang
Xiaolin Huang
AAML
221
4
0
12 Aug 2022
A Sublinear Adversarial Training Algorithm
A Sublinear Adversarial Training AlgorithmInternational Conference on Learning Representations (ICLR), 2022
Yeqi Gao
Lianke Qin
Zhao Song
Yitan Wang
GAN
235
27
0
10 Aug 2022
Ad Hoc Teamwork in the Presence of Adversaries
Ad Hoc Teamwork in the Presence of Adversaries
Ted Fujimoto
Samrat Chatterjee
A. Ganguly
285
4
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09 Aug 2022
Federated Adversarial Learning: A Framework with Convergence Analysis
Federated Adversarial Learning: A Framework with Convergence AnalysisInternational Conference on Machine Learning (ICML), 2022
Xiaoxiao Li
Zhao Song
Jiaming Yang
FedML
308
33
0
07 Aug 2022
Attacking Adversarial Defences by Smoothing the Loss Landscape
Attacking Adversarial Defences by Smoothing the Loss Landscape
Panagiotis Eustratiadis
Henry Gouk
Da Li
Timothy M. Hospedales
AAML
398
5
0
01 Aug 2022
Robust Real-World Image Super-Resolution against Adversarial Attacks
Robust Real-World Image Super-Resolution against Adversarial AttacksACM Multimedia (MM), 2021
N. Babaguchi
John R. Smith
Pengxu Wei
T. Plagemann
Rong Yan
AAML
255
27
0
31 Jul 2022
Robust Trajectory Prediction against Adversarial Attacks
Robust Trajectory Prediction against Adversarial AttacksConference on Robot Learning (CoRL), 2022
Yulong Cao
Danfei Xu
Xinshuo Weng
Zhuoqing Mao
Anima Anandkumar
Chaowei Xiao
Marco Pavone
AAML
210
41
0
29 Jul 2022
Shift-tolerant Perceptual Similarity Metric
Shift-tolerant Perceptual Similarity MetricEuropean Conference on Computer Vision (ECCV), 2022
Abhijay Ghildyal
Yifan Zhang
188
58
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27 Jul 2022
SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and
  Boosting Segmentation Robustness
SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation RobustnessEuropean Conference on Computer Vision (ECCV), 2022
Jindong Gu
Hengshuang Zhao
Volker Tresp
Juil Sock
AAML
296
91
0
25 Jul 2022
Can we achieve robustness from data alone?
Can we achieve robustness from data alone?
Nikolaos Tsilivis
Jingtong Su
Julia Kempe
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323
20
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24 Jul 2022
Decoupled Adversarial Contrastive Learning for Self-supervised
  Adversarial Robustness
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial RobustnessEuropean Conference on Computer Vision (ECCV), 2022
Chaoning Zhang
Kang Zhang
Chenshuang Zhang
Axi Niu
Jiu Feng
Chang D. Yoo
In So Kweon
SSL
170
34
0
22 Jul 2022
Towards Efficient Adversarial Training on Vision Transformers
Towards Efficient Adversarial Training on Vision TransformersEuropean Conference on Computer Vision (ECCV), 2022
Boxi Wu
Jindong Gu
Zhifeng Li
Deng Cai
Xiaofei He
Wei Liu
ViTAAML
253
45
0
21 Jul 2022
Rethinking Textual Adversarial Defense for Pre-trained Language Models
Rethinking Textual Adversarial Defense for Pre-trained Language ModelsIEEE/ACM Transactions on Audio Speech and Language Processing (TASLP), 2022
Jiayi Wang
Rongzhou Bao
Zhuosheng Zhang
Hai Zhao
AAMLSILM
225
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One-vs-the-Rest Loss to Focus on Important Samples in Adversarial
  Training
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial TrainingInternational Conference on Machine Learning (ICML), 2022
Sekitoshi Kanai
Shin'ya Yamaguchi
Masanori Yamada
Hiroshi Takahashi
Kentaro Ohno
Yasutoshi Ida
AAML
284
13
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21 Jul 2022
Tailoring Self-Supervision for Supervised Learning
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Bounding generalization error with input compression: An empirical study
  with infinite-width networks
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Mahmoud Salem
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Assaying Out-Of-Distribution Generalization in Transfer Learning
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Thomas Brox
Bernt Schiele
Bernhard Schölkopf
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Adversarial Pixel Restoration as a Pretext Task for Transferable
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H. Malik
Shahina Kunhimon
Muzammal Naseer
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203
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