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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
Annealing Self-Distillation Rectification Improves Adversarial Training
Annealing Self-Distillation Rectification Improves Adversarial TrainingInternational Conference on Learning Representations (ICLR), 2023
Yuehua Wu
Hung-Jui Wang
Shang-Tse Chen
AAML
273
6
0
20 May 2023
Attacking All Tasks at Once Using Adversarial Examples in Multi-Task Learning
Attacking All Tasks at Once Using Adversarial Examples in Multi-Task Learning
Lijun Zhang
Xiao Liu
Kaleel Mahmood
Caiwen Ding
Hui Guan
AAML
340
1
0
20 May 2023
Attacking Perceptual Similarity Metrics
Attacking Perceptual Similarity Metrics
Abhijay Ghildyal
Yifan Zhang
AAML
259
12
0
15 May 2023
Randomized Smoothing with Masked Inference for Adversarially Robust Text
  Classifications
Randomized Smoothing with Masked Inference for Adversarially Robust Text ClassificationsAnnual Meeting of the Association for Computational Linguistics (ACL), 2023
Han Cheol Moon
Shafiq Joty
Ruochen Zhao
Megh Thakkar
Xu Chi
AAML
236
18
0
11 May 2023
Sharpness-Aware Minimization Alone can Improve Adversarial Robustness
Sharpness-Aware Minimization Alone can Improve Adversarial Robustness
Zeming Wei
Jingyu Zhu
Yihao Zhang
AAML
216
17
0
09 May 2023
Understanding Noise-Augmented Training for Randomized Smoothing
Understanding Noise-Augmented Training for Randomized Smoothing
Ambar Pal
Jeremias Sulam
AAML
361
7
0
08 May 2023
Toward Adversarial Training on Contextualized Language Representation
Toward Adversarial Training on Contextualized Language RepresentationInternational Conference on Learning Representations (ICLR), 2023
Hongqiu Wu
Wenshu Fan
Han Shi
Haizhen Zhao
Hao Fei
AAML
157
15
0
08 May 2023
The Best Defense is Attack: Repairing Semantics in Textual Adversarial
  Examples
The Best Defense is Attack: Repairing Semantics in Textual Adversarial ExamplesConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Heng Yang
Ke Li
AAML
317
4
0
06 May 2023
Towards Prompt-robust Face Privacy Protection via Adversarial Decoupling
  Augmentation Framework
Towards Prompt-robust Face Privacy Protection via Adversarial Decoupling Augmentation Framework
Ruijia Wu
Yuhang Wang
Huafeng Shi
Zhipeng Yu
Yichao Wu
Ding Liang
DiffM
194
11
0
06 May 2023
PTP: Boosting Stability and Performance of Prompt Tuning with
  Perturbation-Based Regularizer
PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based RegularizerConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Lichang Chen
Heng-Chiao Huang
Varun Madhavan
AAML
275
12
0
03 May 2023
On the Security Risks of Knowledge Graph Reasoning
On the Security Risks of Knowledge Graph ReasoningUSENIX Security Symposium (USENIX Security), 2023
Zhaohan Xi
Tianyu Du
Changjiang Li
Ren Pang
S. Ji
Xiapu Luo
Xusheng Xiao
Fenglong Ma
Ting Wang
294
11
0
03 May 2023
Stratified Adversarial Robustness with Rejection
Stratified Adversarial Robustness with RejectionInternational Conference on Machine Learning (ICML), 2023
Jiefeng Chen
Jayaram Raghuram
Jihye Choi
Xi Wu
Yingyu Liang
S. Jha
135
3
0
02 May 2023
Assessing Vulnerabilities of Adversarial Learning Algorithm through
  Poisoning Attacks
Assessing Vulnerabilities of Adversarial Learning Algorithm through Poisoning Attacks
Jingfeng Zhang
Bo Song
Bo Han
Lei Liu
Gang Niu
Masashi Sugiyama
AAML
182
2
0
30 Apr 2023
Generating Adversarial Examples with Task Oriented Multi-Objective
  Optimization
Generating Adversarial Examples with Task Oriented Multi-Objective Optimization
Anh-Vu Bui
Trung Le
He Zhao
Quan Hung Tran
Paul Montague
Dinh Q. Phung
AAML
172
2
0
26 Apr 2023
Individual Fairness in Bayesian Neural Networks
Individual Fairness in Bayesian Neural Networks
Alice Doherty
Matthew Wicker
Luca Laurenti
A. Patané
277
5
0
21 Apr 2023
Certified Adversarial Robustness Within Multiple Perturbation Bounds
Certified Adversarial Robustness Within Multiple Perturbation Bounds
Soumalya Nandi
Sravanti Addepalli
Harsh Rangwani
R. Venkatesh Babu
AAML
167
3
0
20 Apr 2023
Wavelets Beat Monkeys at Adversarial Robustness
Wavelets Beat Monkeys at Adversarial Robustness
Jingtong Su
Julia Kempe
AAMLOOD
118
2
0
19 Apr 2023
Towards the Transferable Audio Adversarial Attack via Ensemble Methods
Towards the Transferable Audio Adversarial Attack via Ensemble Methods
Feng Guo
Zhengyi Sun
Yuxuan Chen
Lei Ju
AAML
161
7
0
18 Apr 2023
RNN-Guard: Certified Robustness Against Multi-frame Attacks for
  Recurrent Neural Networks
RNN-Guard: Certified Robustness Against Multi-frame Attacks for Recurrent Neural Networks
Yunruo Zhang
Tianyu Du
S. Ji
Peng Tang
Shanqing Guo
AAML
210
2
0
17 Apr 2023
Certified Zeroth-order Black-Box Defense with Robust UNet Denoiser
Certified Zeroth-order Black-Box Defense with Robust UNet Denoiser
Astha Verma
A. Subramanyam
Siddhesh Bangar
Naman Lal
R. Shah
Shiníchi Satoh
315
8
0
13 Apr 2023
On the Adversarial Inversion of Deep Biometric Representations
On the Adversarial Inversion of Deep Biometric Representations
Gioacchino Tangari
Shreesh Keskar
Hassan Jameel Asghar
Dali Kaafar
AAML
213
3
0
12 Apr 2023
Certifiable Black-Box Attacks with Randomized Adversarial Examples:
  Breaking Defenses with Provable Confidence
Certifiable Black-Box Attacks with Randomized Adversarial Examples: Breaking Defenses with Provable ConfidenceConference on Computer and Communications Security (CCS), 2023
Hanbin Hong
Xinyu Zhang
Binghui Wang
Zhongjie Ba
Yuan Hong
AAML
282
6
0
10 Apr 2023
Unsupervised Multi-Criteria Adversarial Detection in Deep Image
  Retrieval
Unsupervised Multi-Criteria Adversarial Detection in Deep Image RetrievalSecurity and Privacy in Communication Networks (SecureComm), 2023
Yanru Xiao
Cong Wang
Xing Gao
AAML
251
0
0
09 Apr 2023
Robust Deep Learning Models Against Semantic-Preserving Adversarial
  Attack
Robust Deep Learning Models Against Semantic-Preserving Adversarial AttackIEEE International Joint Conference on Neural Network (IJCNN), 2023
Dashan Gao
Yunce Zhao
Yinghua Yao
Zeqi Zhang
Bifei Mao
Xin Yao
AAML
139
1
0
08 Apr 2023
Improving Fast Adversarial Training with Prior-Guided Knowledge
Improving Fast Adversarial Training with Prior-Guided KnowledgeIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Yang Liu
Yong Zhang
Xingxing Wei
Baoyuan Wu
Ke Ma
Jue Wang
Xiaochun Cao
AAML
272
49
0
01 Apr 2023
Generating Adversarial Samples in Mini-Batches May Be Detrimental To
  Adversarial Robustness
Generating Adversarial Samples in Mini-Batches May Be Detrimental To Adversarial Robustness
T. Redgrave
Colton R. Crum
AAML
85
1
0
30 Mar 2023
Fooling the Image Dehazing Models by First Order Gradient
Fooling the Image Dehazing Models by First Order Gradient
Jie Gui
Xiaofeng Cong
Chengwei Peng
Yuan Yan Tang
James T. Kwok
AAML
170
17
0
30 Mar 2023
Beyond Empirical Risk Minimization: Local Structure Preserving
  Regularization for Improving Adversarial Robustness
Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness
Wei Wei
Jiahuan Zhou
Yingying Wu
AAML
139
0
0
29 Mar 2023
Provable Robustness for Streaming Models with a Sliding Window
Provable Robustness for Streaming Models with a Sliding Window
Aounon Kumar
Vinu Sankar Sadasivan
Soheil Feizi
OODAAMLAI4TS
246
1
0
28 Mar 2023
Learning Iterative Neural Optimizers for Image Steganography
Learning Iterative Neural Optimizers for Image SteganographyInternational Conference on Learning Representations (ICLR), 2023
Xiangyu Chen
Varsha Kishore
Kilian Q. Weinberger
122
10
0
27 Mar 2023
Anti-DreamBooth: Protecting users from personalized text-to-image
  synthesis
Anti-DreamBooth: Protecting users from personalized text-to-image synthesisIEEE International Conference on Computer Vision (ICCV), 2023
T. Le
Hao Phung
Thuan Hoang Nguyen
Quan Dao
Ngoc N. Tran
Anh Tran
370
134
0
27 Mar 2023
CFA: Class-wise Calibrated Fair Adversarial Training
CFA: Class-wise Calibrated Fair Adversarial TrainingComputer Vision and Pattern Recognition (CVPR), 2023
Zeming Wei
Yifei Wang
Yiwen Guo
Yisen Wang
AAML
252
75
0
25 Mar 2023
Enhancing Multiple Reliability Measures via Nuisance-extended
  Information Bottleneck
Enhancing Multiple Reliability Measures via Nuisance-extended Information BottleneckComputer Vision and Pattern Recognition (CVPR), 2023
Jongheon Jeong
Sihyun Yu
Hankook Lee
Jinwoo Shin
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179
1
0
24 Mar 2023
Improved Adversarial Training Through Adaptive Instance-wise Loss
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Improved Adversarial Training Through Adaptive Instance-wise Loss Smoothing
Lin Li
Michael W. Spratling
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334
4
0
24 Mar 2023
PIAT: Parameter Interpolation based Adversarial Training for Image
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PIAT: Parameter Interpolation based Adversarial Training for Image Classification
Kun He
Xin Liu
Yichen Yang
Zhou Qin
Weigao Wen
Hui Xue
John E. Hopcroft
AAML
164
0
0
24 Mar 2023
Feature Separation and Recalibration for Adversarial Robustness
Feature Separation and Recalibration for Adversarial RobustnessComputer Vision and Pattern Recognition (CVPR), 2023
Woo Jae Kim
Y. Cho
Junsik Jung
Sung-eui Yoon
AAML
354
35
0
24 Mar 2023
Generalist: Decoupling Natural and Robust Generalization
Generalist: Decoupling Natural and Robust GeneralizationComputer Vision and Pattern Recognition (CVPR), 2023
Hongjun Wang
Yisen Wang
OODAAML
220
20
0
24 Mar 2023
State-of-the-art optical-based physical adversarial attacks for deep
  learning computer vision systems
State-of-the-art optical-based physical adversarial attacks for deep learning computer vision systemsExpert systems with applications (ESWA), 2023
Jun-bin Fang
You Jiang
Canjian Jiang
Z. L. Jiang
Siu-Ming Yiu
Chuanyi Liu
AAML
213
25
0
22 Mar 2023
Bridging Optimal Transport and Jacobian Regularization by Optimal
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Bridging Optimal Transport and Jacobian Regularization by Optimal Trajectory for Enhanced Adversarial DefenseAsian Conference on Computer Vision (ACCV), 2023
B. Le
Shahroz Tariq
Simon S. Woo
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168
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21 Mar 2023
Boosting Verified Training for Robust Image Classifications via
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Boosting Verified Training for Robust Image Classifications via AbstractionComputer Vision and Pattern Recognition (CVPR), 2023
Zhaodi Zhang
Zhiyi Xue
Yang Chen
Si Liu
Yueling Zhang
Qingbin Liu
Min Zhang
249
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21 Mar 2023
GNN-Ensemble: Towards Random Decision Graph Neural Networks
GNN-Ensemble: Towards Random Decision Graph Neural NetworksBigData Congress [Services Society] (BSS), 2023
Wenqi Wei
Mu Qiao
D. Jadav
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173
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20 Mar 2023
Adversarial Attacks against Binary Similarity Systems
Adversarial Attacks against Binary Similarity SystemsIEEE Access (IEEE Access), 2023
Gianluca Capozzi
Daniele Cono DÉlia
Giuseppe Antonio Di Luna
Leonardo Querzoni
AAML
176
4
0
20 Mar 2023
SeiT: Storage-Efficient Vision Training with Tokens Using 1% of Pixel
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SeiT: Storage-Efficient Vision Training with Tokens Using 1% of Pixel StorageIEEE International Conference on Computer Vision (ICCV), 2023
Song Park
Sanghyuk Chun
Byeongho Heo
Wonjae Kim
Sangdoo Yun
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283
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20 Mar 2023
Robust Evaluation of Diffusion-Based Adversarial Purification
Robust Evaluation of Diffusion-Based Adversarial PurificationIEEE International Conference on Computer Vision (ICCV), 2023
M. Lee
Dongwoo Kim
456
87
0
16 Mar 2023
Review on the Feasibility of Adversarial Evasion Attacks and Defenses
  for Network Intrusion Detection Systems
Review on the Feasibility of Adversarial Evasion Attacks and Defenses for Network Intrusion Detection Systems
Islam Debicha
Benjamin Cochez
Tayeb Kenaza
Thibault Debatty
Jean-Michel Dricot
Wim Mees
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185
8
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13 Mar 2023
Adaptive Local Adversarial Attacks on 3D Point Clouds for Augmented
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Weiquan Liu
Shijun Zheng
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213
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Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A
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Yulong Wang
Tong Sun
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W. Ni
Ekram Hossain
H. Vincent Poor
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278
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Stateful Defenses for Machine Learning Models Are Not Yet Secure Against
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Ashish Hooda
Neal Mangaokar
Kassem Fawaz
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285
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Do we need entire training data for adversarial training?
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Vipul Gupta
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219
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Efficient Certified Training and Robustness Verification of Neural ODEs
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262
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