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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 / 1,982 papers shown
Rethinking Machine Unlearning for Large Language Models
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Sijia Liu
Yuanshun Yao
Jinghan Jia
Stephen Casper
Nathalie Baracaldo
...
Hang Li
Kush R. Varshney
Mohit Bansal
Sanmi Koyejo
Yang Liu
AILawMU
428
200
0
13 Feb 2024
Accuracy of TextFooler black box adversarial attacks on 01 loss sign
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Accuracy of TextFooler black box adversarial attacks on 01 loss sign activation neural network ensemble
Yunzhe Xue
Usman Roshan
AAML
147
0
0
12 Feb 2024
Accelerated Smoothing: A Scalable Approach to Randomized Smoothing
Accelerated Smoothing: A Scalable Approach to Randomized Smoothing
Devansh Bhardwaj
Kshitiz Kaushik
Sarthak Gupta
AAML
336
0
0
12 Feb 2024
A Random Ensemble of Encrypted Vision Transformers for Adversarially
  Robust Defense
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust DefenseIEEE Access (IEEE Access), 2024
Ryota Iijima
Sayaka Shiota
Hitoshi Kiya
298
9
0
11 Feb 2024
HarmBench: A Standardized Evaluation Framework for Automated Red Teaming
  and Robust Refusal
HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal
Mantas Mazeika
Long Phan
Xuwang Yin
Andy Zou
Zifan Wang
...
Nathaniel Li
Steven Basart
Bo Li
David A. Forsyth
Dan Hendrycks
AAML
359
732
0
06 Feb 2024
FINEST: Stabilizing Recommendations by Rank-Preserving Fine-Tuning
FINEST: Stabilizing Recommendations by Rank-Preserving Fine-TuningACM Transactions on Knowledge Discovery from Data (TKDD), 2024
Sejoon Oh
Berk Ustun
Julian McAuley
Srijan Kumar
182
2
0
05 Feb 2024
Unraveling the Key of Machine Learning Solutions for Android Malware
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Unraveling the Key of Machine Learning Solutions for Android Malware Detection
Jiahao Liu
Jun Zeng
Fabio Pierazzi
Lorenzo Cavallaro
Zhenkai Liang
AAML
188
11
0
05 Feb 2024
Your Diffusion Model is Secretly a Certifiably Robust Classifier
Your Diffusion Model is Secretly a Certifiably Robust Classifier
Huanran Chen
Yinpeng Dong
Shitong Shao
Zhongkai Hao
Xiao Yang
Hang Su
Jun Zhu
DiffM
385
6
0
04 Feb 2024
MixedNUTS: Training-Free Accuracy-Robustness Balance via Nonlinearly
  Mixed Classifiers
MixedNUTS: Training-Free Accuracy-Robustness Balance via Nonlinearly Mixed Classifiers
Yatong Bai
Mo Zhou
Vishal M. Patel
Somayeh Sojoudi
AAML
402
16
0
03 Feb 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Wenqi Wei
Ling Liu
361
44
0
02 Feb 2024
Tropical Decision Boundaries for Neural Networks Are Robust Against
  Adversarial Attacks
Tropical Decision Boundaries for Neural Networks Are Robust Against Adversarial Attacks
Kurt Pasque
Christopher Teska
Ruriko Yoshida
Keiji Miura
Jefferson Huang
AAML
322
4
0
01 Feb 2024
Adversarial Training on Purification (AToP): Advancing Both Robustness
  and Generalization
Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization
Guang Lin
Chao Li
Jianhai Zhang
Toshihisa Tanaka
Qibin Zhao
367
22
0
29 Jan 2024
Securing Recommender System via Cooperative Training
Securing Recommender System via Cooperative TrainingWorld wide web (Bussum) (WWW), 2023
Qingyang Wang
Chenwang Wu
Defu Lian
Enhong Chen
AAML
218
4
0
23 Jan 2024
Robustness to distribution shifts of compressed networks for edge
  devices
Robustness to distribution shifts of compressed networks for edge devices
Lulan Shen
Ali Edalati
Brett H. Meyer
Warren Gross
James J. Clark
175
0
0
22 Jan 2024
How Robust Are Energy-Based Models Trained With Equilibrium Propagation?
How Robust Are Energy-Based Models Trained With Equilibrium Propagation?
Siddharth Mansingh
Michal Kucer
Garrett Kenyon
Juston S. Moore
Michael Teti
AAML
263
2
0
21 Jan 2024
Adversarial Examples are Misaligned in Diffusion Model Manifolds
Adversarial Examples are Misaligned in Diffusion Model ManifoldsIEEE International Joint Conference on Neural Network (IJCNN), 2024
P. Lorenz
Ricard Durall
Jansi Keuper
DiffM
463
1
0
12 Jan 2024
Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial
  Robustness
Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial RobustnessComputer Vision and Pattern Recognition (CVPR), 2024
Sibo Wang
Jie Zhang
Zheng Yuan
Shiguang Shan
VLM
345
46
0
09 Jan 2024
Calibration Attacks: A Comprehensive Study of Adversarial Attacks on
  Model Confidence
Calibration Attacks: A Comprehensive Study of Adversarial Attacks on Model Confidence
Stephen Obadinma
Xiaodan Zhu
Ziqiao Wang
AAML
265
2
0
05 Jan 2024
Adversarial Attacks on Image Classification Models: Analysis and Defense
Adversarial Attacks on Image Classification Models: Analysis and Defense
Jaydip Sen
Abhiraj Sen
Ananda Chatterjee
AAML
161
6
0
28 Dec 2023
BlackboxBench: A Comprehensive Benchmark of Black-box Adversarial Attacks
BlackboxBench: A Comprehensive Benchmark of Black-box Adversarial Attacks
Meixi Zheng
Xuanchen Yan
Zihao Zhu
Hongrui Chen
Baoyuan Wu
ELMMLAUAAML
415
17
0
28 Dec 2023
ARBiBench: Benchmarking Adversarial Robustness of Binarized Neural
  Networks
ARBiBench: Benchmarking Adversarial Robustness of Binarized Neural Networks
Peng Zhao
Jiehua Zhang
Bowen Peng
Longguang Wang
Yingmei Wei
Yu Liu
Li Liu
AAML
336
2
0
21 Dec 2023
The Ultimate Combo: Boosting Adversarial Example Transferability by
  Composing Data Augmentations
The Ultimate Combo: Boosting Adversarial Example Transferability by Composing Data Augmentations
Zebin Yun
Achi-Or Weingarten
Eyal Ronen
Mahmood Sharif
214
2
0
18 Dec 2023
Exploring Transferability for Randomized Smoothing
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Kai Qiu
Huishuai Zhang
Zhirong Wu
Stephen Lin
AAML
152
1
0
14 Dec 2023
May the Noise be with you: Adversarial Training without Adversarial
  Examples
May the Noise be with you: Adversarial Training without Adversarial Examples
Ayoub Arous
A. F. López-Lopera
Nael B. Abu-Ghazaleh
Ihsen Alouani
AAMLOOD
102
0
0
12 Dec 2023
MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness
MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness
Xiaoyun Xu
Shujian Yu
Jingzheng Wu
S. Picek
AAML
609
8
0
08 Dec 2023
On the Robustness of Large Multimodal Models Against Image Adversarial
  Attacks
On the Robustness of Large Multimodal Models Against Image Adversarial Attacks
Xuanimng Cui
Alejandro Aparcedo
Young Kyun Jang
Ser-Nam Lim
AAMLVLM
274
79
0
06 Dec 2023
A Simple Framework to Enhance the Adversarial Robustness of Deep
  Learning-based Intrusion Detection System
A Simple Framework to Enhance the Adversarial Robustness of Deep Learning-based Intrusion Detection SystemComputers & security (CS), 2023
Xinwei Yuan
Shu Han
Wei Huang
Hongliang Ye
Xianglong Kong
Fan Zhang
AAML
188
48
0
06 Dec 2023
Generating Visually Realistic Adversarial Patch
Generating Visually Realistic Adversarial Patch
Xiaosen Wang
Kunyu Wang
AAML
207
1
0
05 Dec 2023
Singular Regularization with Information Bottleneck Improves Model's
  Adversarial Robustness
Singular Regularization with Information Bottleneck Improves Model's Adversarial Robustness
Guanlin Li
Naishan Zheng
Man Zhou
Jie Zhang
Tianwei Zhang
AAML
139
0
0
04 Dec 2023
Adversarial Medical Image with Hierarchical Feature Hiding
Adversarial Medical Image with Hierarchical Feature HidingIEEE Transactions on Medical Imaging (TMI), 2023
Qingsong Yao
Zecheng He
Yuexiang Li
Yi Lin
Kai Ma
Yefeng Zheng
S. Kevin Zhou
MedImAAML
274
8
0
04 Dec 2023
Topology-Preserving Adversarial Training
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Xiaoyue Mi
Fan Tang
Yepeng Weng
Danding Wang
Juan Cao
Sheng Tang
Peng Li
Yang Liu
281
1
0
29 Nov 2023
Improving the Robustness of Transformer-based Large Language Models with
  Dynamic Attention
Improving the Robustness of Transformer-based Large Language Models with Dynamic AttentionNetwork and Distributed System Security Symposium (NDSS), 2023
Lujia Shen
Yuwen Pu
R. Beyah
Changjiang Li
Xuhong Zhang
Chunpeng Ge
Ting Wang
AAML
187
10
0
29 Nov 2023
RADAP: A Robust and Adaptive Defense Against Diverse Adversarial Patches
  on Face Recognition
RADAP: A Robust and Adaptive Defense Against Diverse Adversarial Patches on Face Recognition
Xiaoliang Liu
Shen Furao
Jian Zhao
Changhai Nie
AAML
172
5
0
29 Nov 2023
Efficient Key-Based Adversarial Defense for ImageNet by Using
  Pre-trained Model
Efficient Key-Based Adversarial Defense for ImageNet by Using Pre-trained ModelIEEE Open Journal of Signal Processing (IEEE Open J. Signal Process.), 2023
AprilPyone Maungmaung
Isao Echizen
Hitoshi Kiya
VLMAAML
181
1
0
28 Nov 2023
On robust overfitting: adversarial training induced distribution matters
On robust overfitting: adversarial training induced distribution matters
Runzhi Tian
Yongyi Mao
OOD
292
1
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Instruct2Attack: Language-Guided Semantic Adversarial Attacks
Instruct2Attack: Language-Guided Semantic Adversarial Attacks
Jiang-Long Liu
Chen Wei
Yuxiang Guo
Heng Yu
Yaoyao Liu
Soheil Feizi
Chun Pong Lau
Rama Chellappa
DiffMAAML
223
11
0
27 Nov 2023
Adversarial Purification of Information Masking
Adversarial Purification of Information Masking
Sitong Liu
Z. Lian
Shuangquan Zhang
Liang Xiao
AAML
200
1
0
26 Nov 2023
Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-Off
Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-OffConference on Learning for Dynamics & Control (L4DC), 2023
Yatong Bai
Brendon G. Anderson
Somayeh Sojoudi
AAML
288
2
0
26 Nov 2023
Adversarial defense based on distribution transfer
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Jiahao Chen
Diqun Yan
Li Dong
187
0
0
23 Nov 2023
Explaining high-dimensional text classifiers
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Odelia Melamed
Rich Caruana
186
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Fast Certification of Vision-Language Models Using Incremental
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Ashutosh Nirala
Ameya Joshi
Chinmay Hegde
S Sarkar
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343
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0
15 Nov 2023
Adversarially Robust Spiking Neural Networks Through Conversion
Adversarially Robust Spiking Neural Networks Through Conversion
Ozan Özdenizci
Robert Legenstein
AAML
363
15
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15 Nov 2023
On The Relationship Between Universal Adversarial Attacks And Sparse
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On The Relationship Between Universal Adversarial Attacks And Sparse RepresentationsIEEE Open Journal of Signal Processing (IEEE Open J. Signal Process.), 2023
Dana Weitzner
Raja Giryes
AAML
278
0
0
14 Nov 2023
Towards Improving Robustness Against Common Corruptions in Object
  Detectors Using Adversarial Contrastive Learning
Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning
Shashank Kotyan
Danilo Vasconcellos Vargas
AAML
207
0
0
14 Nov 2023
Upper and lower bounds for the Lipschitz constant of random neural networks
Upper and lower bounds for the Lipschitz constant of random neural networks
Paul Geuchen
Dominik Stöger
Dominik Stöger
Felix Voigtlaender
AAML
491
0
0
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Intriguing Properties of Data Attribution on Diffusion Models
Intriguing Properties of Data Attribution on Diffusion ModelsInternational Conference on Learning Representations (ICLR), 2023
Xiaosen Zheng
Tianyu Pang
Chao Du
Jing Jiang
Min Lin
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393
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Exploring Geometry of Blind Spots in Vision Models
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S. Balasubramanian
Gaurang Sriramanan
Vinu Sankar Sadasivan
Soheil Feizi
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222
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Adversarial Attacks and Defenses in Large Language Models: Old and New
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Leo Schwinn
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Stephan Günnemann
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236
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Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from
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282
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Adversarial Examples Are Not Real Features
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Ang Li
Yifei Wang
Yiwen Guo
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629
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