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

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

1 February 2018
Anish Athalye
Nicholas Carlini
D. Wagner
    AAML
ArXivPDFHTML

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

50 / 736 papers shown
Title
All You Need is RAW: Defending Against Adversarial Attacks with Camera
  Image Pipelines
All You Need is RAW: Defending Against Adversarial Attacks with Camera Image Pipelines
Yuxuan Zhang
B. Dong
Felix Heide
AAML
26
8
0
16 Dec 2021
On the Convergence and Robustness of Adversarial Training
On the Convergence and Robustness of Adversarial Training
Yisen Wang
Xingjun Ma
James Bailey
Jinfeng Yi
Bowen Zhou
Quanquan Gu
AAML
212
345
0
15 Dec 2021
Temporal Shuffling for Defending Deep Action Recognition Models against
  Adversarial Attacks
Temporal Shuffling for Defending Deep Action Recognition Models against Adversarial Attacks
Jaehui Hwang
Huan Zhang
Jun-Ho Choi
Cho-Jui Hsieh
Jong-Seok Lee
AAML
19
5
0
15 Dec 2021
On the Impact of Hard Adversarial Instances on Overfitting in
  Adversarial Training
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
Chen Liu
Zhichao Huang
Mathieu Salzmann
Tong Zhang
Sabine Süsstrunk
AAML
23
13
0
14 Dec 2021
Triangle Attack: A Query-efficient Decision-based Adversarial Attack
Triangle Attack: A Query-efficient Decision-based Adversarial Attack
Xiaosen Wang
Zeliang Zhang
Kangheng Tong
Dihong Gong
Kun He
Zhifeng Li
Wei Liu
AAML
24
56
0
13 Dec 2021
Interpolated Joint Space Adversarial Training for Robust and
  Generalizable Defenses
Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses
Chun Pong Lau
Jiang-Long Liu
Hossein Souri
Wei-An Lin
S. Feizi
Ramalingam Chellappa
AAML
31
12
0
12 Dec 2021
RamBoAttack: A Robust Query Efficient Deep Neural Network Decision
  Exploit
RamBoAttack: A Robust Query Efficient Deep Neural Network Decision Exploit
Viet Vo
Ehsan Abbasnejad
Damith C. Ranasinghe
AAML
25
9
0
10 Dec 2021
Mutual Adversarial Training: Learning together is better than going
  alone
Mutual Adversarial Training: Learning together is better than going alone
Jiang-Long Liu
Chun Pong Lau
Hossein Souri
S. Feizi
Ramalingam Chellappa
OOD
AAML
48
24
0
09 Dec 2021
SoK: Anti-Facial Recognition Technology
SoK: Anti-Facial Recognition Technology
Emily Wenger
Shawn Shan
Haitao Zheng
Ben Y. Zhao
PICV
32
13
0
08 Dec 2021
Segment and Complete: Defending Object Detectors against Adversarial
  Patch Attacks with Robust Patch Detection
Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection
Jiangjiang Liu
Alexander Levine
Chun Pong Lau
Ramalingam Chellappa
S. Feizi
AAML
32
77
0
08 Dec 2021
AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural
  Networks
AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural Networks
Huu Le
R. Høier
Che-Tsung Lin
Christopher Zach
55
17
0
06 Dec 2021
Stochastic Local Winner-Takes-All Networks Enable Profound Adversarial
  Robustness
Stochastic Local Winner-Takes-All Networks Enable Profound Adversarial Robustness
Konstantinos P. Panousis
S. Chatzis
Sergios Theodoridis
BDL
AAML
66
11
0
05 Dec 2021
On the Existence of the Adversarial Bayes Classifier (Extended Version)
On the Existence of the Adversarial Bayes Classifier (Extended Version)
Pranjal Awasthi
Natalie Frank
M. Mohri
31
24
0
03 Dec 2021
Certified Adversarial Defenses Meet Out-of-Distribution Corruptions:
  Benchmarking Robustness and Simple Baselines
Certified Adversarial Defenses Meet Out-of-Distribution Corruptions: Benchmarking Robustness and Simple Baselines
Jiachen Sun
Akshay Mehra
B. Kailkhura
Pin-Yu Chen
Dan Hendrycks
Jihun Hamm
Z. Morley Mao
AAML
41
21
0
01 Dec 2021
Adv-4-Adv: Thwarting Changing Adversarial Perturbations via Adversarial
  Domain Adaptation
Adv-4-Adv: Thwarting Changing Adversarial Perturbations via Adversarial Domain Adaptation
Tianyue Zheng
Zhe Chen
Shuya Ding
Chao Cai
Jun Luo
AAML
35
5
0
01 Dec 2021
Push Stricter to Decide Better: A Class-Conditional Feature Adaptive
  Framework for Improving Adversarial Robustness
Push Stricter to Decide Better: A Class-Conditional Feature Adaptive Framework for Improving Adversarial Robustness
Jia-Li Yin
Lehui Xie
Wanqing Zhu
Ximeng Liu
Bo-Hao Chen
TTA
AAML
31
3
0
01 Dec 2021
Mitigating Adversarial Attacks by Distributing Different Copies to
  Different Users
Mitigating Adversarial Attacks by Distributing Different Copies to Different Users
Jiyi Zhang
Hansheng Fang
W. Tann
Ke Xu
Chengfang Fang
E. Chang
AAML
34
3
0
30 Nov 2021
Pyramid Adversarial Training Improves ViT Performance
Pyramid Adversarial Training Improves ViT Performance
Charles Herrmann
Kyle Sargent
Lu Jiang
Ramin Zabih
Huiwen Chang
Ce Liu
Dilip Krishnan
Deqing Sun
ViT
32
56
0
30 Nov 2021
Adaptive Image Transformations for Transfer-based Adversarial Attack
Adaptive Image Transformations for Transfer-based Adversarial Attack
Zheng Yuan
Jie Zhang
Shiguang Shan
OOD
24
25
0
27 Nov 2021
Clustering Effect of (Linearized) Adversarial Robust Models
Clustering Effect of (Linearized) Adversarial Robust Models
Yang Bai
Xin Yan
Yong Jiang
Shutao Xia
Yisen Wang
OOD
AAML
44
5
0
25 Nov 2021
Subspace Adversarial Training
Subspace Adversarial Training
Tao Li
Yingwen Wu
Sizhe Chen
Kun Fang
Xiaolin Huang
AAML
OOD
44
56
0
24 Nov 2021
Medical Aegis: Robust adversarial protectors for medical images
Medical Aegis: Robust adversarial protectors for medical images
Qingsong Yao
Zecheng He
S. Kevin Zhou
AAML
MedIm
30
2
0
22 Nov 2021
Neural Population Geometry Reveals the Role of Stochasticity in Robust
  Perception
Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception
Joel Dapello
J. Feather
Hang Le
Tiago Marques
David D. Cox
Josh H. McDermott
J. DiCarlo
SueYeon Chung
AAML
OOD
19
25
0
12 Nov 2021
Data Augmentation Can Improve Robustness
Data Augmentation Can Improve Robustness
Sylvestre-Alvise Rebuffi
Sven Gowal
D. A. Calian
Florian Stimberg
Olivia Wiles
Timothy A. Mann
AAML
34
271
0
09 Nov 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated
  Channel Maps
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps
Muhammad Awais
Fengwei Zhou
Chuanlong Xie
Jiawei Li
Sung-Ho Bae
Zhenguo Li
AAML
43
17
0
09 Nov 2021
Robust and Information-theoretically Safe Bias Classifier against
  Adversarial Attacks
Robust and Information-theoretically Safe Bias Classifier against Adversarial Attacks
Lijia Yu
Xiao-Shan Gao
AAML
21
5
0
08 Nov 2021
LTD: Low Temperature Distillation for Robust Adversarial Training
LTD: Low Temperature Distillation for Robust Adversarial Training
Erh-Chung Chen
Che-Rung Lee
AAML
27
26
0
03 Nov 2021
Meta-Learning the Search Distribution of Black-Box Random Search Based
  Adversarial Attacks
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks
Maksym Yatsura
J. H. Metzen
Matthias Hein
OOD
26
14
0
02 Nov 2021
Training Certifiably Robust Neural Networks with Efficient Local
  Lipschitz Bounds
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds
Yujia Huang
Huan Zhang
Yuanyuan Shi
J Zico Kolter
Anima Anandkumar
41
76
0
02 Nov 2021
ε-weakened Robustness of Deep Neural Networks
ε-weakened Robustness of Deep Neural Networks
Pei Huang
Yuting Yang
Minghao Liu
Fuqi Jia
Feifei Ma
Jian Zhang
AAML
27
18
0
29 Oct 2021
Towards Evaluating the Robustness of Neural Networks Learned by
  Transduction
Towards Evaluating the Robustness of Neural Networks Learned by Transduction
Jiefeng Chen
Xi Wu
Yang Guo
Yingyu Liang
S. Jha
ELM
AAML
20
15
0
27 Oct 2021
Adversarial Attacks and Defenses for Social Network Text Processing
  Applications: Techniques, Challenges and Future Research Directions
Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directions
I. Alsmadi
Kashif Ahmad
Mahmoud Nazzal
Firoj Alam
Ala I. Al-Fuqaha
Abdallah Khreishah
A. Algosaibi
AAML
37
16
0
26 Oct 2021
Adversarial Robustness in Multi-Task Learning: Promises and Illusions
Adversarial Robustness in Multi-Task Learning: Promises and Illusions
Salah Ghamizi
Maxime Cordy
Mike Papadakis
Yves Le Traon
OOD
AAML
31
18
0
26 Oct 2021
Ensemble Federated Adversarial Training with Non-IID data
Ensemble Federated Adversarial Training with Non-IID data
Shuang Luo
Didi Zhu
Zexi Li
Chao-Xiang Wu
FedML
33
7
0
26 Oct 2021
ADC: Adversarial attacks against object Detection that evade Context
  consistency checks
ADC: Adversarial attacks against object Detection that evade Context consistency checks
Mingjun Yin
Shasha Li
Chengyu Song
Ulugbek S. Kamilov
Amit K. Roy-Chowdhury
S. Krishnamurthy
AAML
29
22
0
24 Oct 2021
A Layer-wise Adversarial-aware Quantization Optimization for Improving
  Robustness
A Layer-wise Adversarial-aware Quantization Optimization for Improving Robustness
Chang Song
Riya Ranjan
H. Li
MQ
21
4
0
23 Oct 2021
Improving Robustness using Generated Data
Improving Robustness using Generated Data
Sven Gowal
Sylvestre-Alvise Rebuffi
Olivia Wiles
Florian Stimberg
D. A. Calian
Timothy A. Mann
36
294
0
18 Oct 2021
Poison Forensics: Traceback of Data Poisoning Attacks in Neural Networks
Poison Forensics: Traceback of Data Poisoning Attacks in Neural Networks
Shawn Shan
A. Bhagoji
Haitao Zheng
Ben Y. Zhao
AAML
94
50
0
13 Oct 2021
Parameterizing Activation Functions for Adversarial Robustness
Parameterizing Activation Functions for Adversarial Robustness
Sihui Dai
Saeed Mahloujifar
Prateek Mittal
AAML
44
32
0
11 Oct 2021
Adversarial Token Attacks on Vision Transformers
Adversarial Token Attacks on Vision Transformers
Ameya Joshi
Gauri Jagatap
C. Hegde
ViT
30
19
0
08 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural
  Networks
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
Hanxun Huang
Yisen Wang
S. Erfani
Quanquan Gu
James Bailey
Xingjun Ma
AAML
TPM
48
100
0
07 Oct 2021
Label Noise in Adversarial Training: A Novel Perspective to Study Robust
  Overfitting
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting
Chengyu Dong
Liyuan Liu
Jingbo Shang
NoLa
AAML
66
18
0
07 Oct 2021
Improving Adversarial Robustness for Free with Snapshot Ensemble
Improving Adversarial Robustness for Free with Snapshot Ensemble
Yihao Wang
AAML
UQCV
17
1
0
07 Oct 2021
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep
  Spiking Neural Networks by Training with Crafted Input Noise
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise
Souvik Kundu
Massoud Pedram
P. Beerel
AAML
22
71
0
06 Oct 2021
Calibrated Adversarial Training
Calibrated Adversarial Training
Tianjin Huang
Vlado Menkovski
Yulong Pei
Mykola Pechenizkiy
AAML
64
3
0
01 Oct 2021
Mitigating Black-Box Adversarial Attacks via Output Noise Perturbation
Mitigating Black-Box Adversarial Attacks via Output Noise Perturbation
Manjushree B. Aithal
Xiaohua Li
AAML
60
6
0
30 Sep 2021
Back in Black: A Comparative Evaluation of Recent State-Of-The-Art
  Black-Box Attacks
Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attacks
Kaleel Mahmood
Rigel Mahmood
Ethan Rathbun
Marten van Dijk
AAML
19
22
0
29 Sep 2021
MUTEN: Boosting Gradient-Based Adversarial Attacks via Mutant-Based
  Ensembles
MUTEN: Boosting Gradient-Based Adversarial Attacks via Mutant-Based Ensembles
Yuejun Guo
Qiang Hu
Maxime Cordy
Michail Papadakis
Yves Le Traon
AAML
32
2
0
27 Sep 2021
Adversarial Transfer Attacks With Unknown Data and Class Overlap
Adversarial Transfer Attacks With Unknown Data and Class Overlap
Luke E. Richards
A. Nguyen
Ryan Capps
Steven D. Forsythe
Cynthia Matuszek
Edward Raff
AAML
41
7
0
23 Sep 2021
CC-Cert: A Probabilistic Approach to Certify General Robustness of
  Neural Networks
CC-Cert: A Probabilistic Approach to Certify General Robustness of Neural Networks
Mikhail Aleksandrovich Pautov
Nurislam Tursynbek
Marina Munkhoeva
Nikita Muravev
Aleksandr Petiushko
Ivan Oseledets
AAML
52
16
0
22 Sep 2021
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