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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
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Certified $\ell_2$ Attribution Robustness via Uniformly Smoothed
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239
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Evaluating Adversarial Robustness in the Spatial Frequency Domain
Evaluating Adversarial Robustness in the Spatial Frequency Domain
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Chin-Yuan Yeh
Hsi-Wen Chen
Ming-Syan Chen
223
0
0
10 May 2024
Towards Accurate and Robust Architectures via Neural Architecture Search
Towards Accurate and Robust Architectures via Neural Architecture SearchComputer Vision and Pattern Recognition (CVPR), 2024
Yuwei Ou
Yuqi Feng
Yanan Sun
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196
9
0
09 May 2024
Sparse-PGD: A Unified Framework for Sparse Adversarial Perturbations Generation
Sparse-PGD: A Unified Framework for Sparse Adversarial Perturbations GenerationIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024
Xuyang Zhong
Yixiao Huang
AAML
406
1
0
08 May 2024
Cutting through buggy adversarial example defenses: fixing 1 line of
  code breaks Sabre
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Nicholas Carlini
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107
3
0
06 May 2024
Certification of Speaker Recognition Models to Additive Perturbations
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Dmitrii Korzh
Elvir Karimov
Mikhail Aleksandrovich Pautov
Oleg Y. Rogov
Ivan Oseledets
285
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0
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Exploring the Robustness of In-Context Learning with Noisy Labels
Exploring the Robustness of In-Context Learning with Noisy Labels
Chen Cheng
Xinzhi Yu
Haodong Wen
Jinsong Sun
Guanzhang Yue
Yihao Zhang
Zeming Wei
NoLa
339
12
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Attacking Bayes: On the Adversarial Robustness of Bayesian Neural
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Yunzhen Feng
Tim G. J. Rudner
Nikolaos Tsilivis
Julia Kempe
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334
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Steal Now and Attack Later: Evaluating Robustness of Object Detection
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Pin-Yu Chen
I-Hsin Chung
Che-Rung Lee
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202
2
0
24 Apr 2024
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Kezhao Liu
Yao Xiao
Ziyi Dong
Xiaogang Xu
Pengxu Wei
Liang Lin
DiffM
271
2
0
22 Apr 2024
Struggle with Adversarial Defense? Try Diffusion
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Yujie Li
Yanbin Wang
Peiyue Li
Bin Liu
Jianguo Sun
Yifan Jia
Wenrui Ma
DiffM
253
1
0
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Chaojian Yu
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260
14
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LRR: Language-Driven Resamplable Continuous Representation against
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Jianlang Chen
Xuhong Ren
Qing Guo
Felix Juefei Xu
Di Lin
Wei Feng
Lei Ma
Jianjun Zhao
241
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Arthur Drichel
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197
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179
13
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Certified PEFTSmoothing: Parameter-Efficient Fine-Tuning with Randomized
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Chengyan Fu
Wenjie Wang
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276
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BruSLeAttack: A Query-Efficient Score-Based Black-Box Sparse Adversarial
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Viet Vo
Ehsan Abbasnejad
Damith C. Ranasinghe
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318
10
0
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Defense without Forgetting: Continual Adversarial Defense with
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Zhongyun Hua
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269
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Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks
Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive AttacksInternational Conference on Learning Representations (ICLR), 2024
Maksym Andriushchenko
Francesco Croce
Nicolas Flammarion
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793
374
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Embodied Active Defense: Leveraging Recurrent Feedback to Counter
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Lingxuan Wu
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211
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381
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201
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240
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235
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228
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Robustness Verifcation in Neural Networks
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ADAPT to Robustify Prompt Tuning Vision Transformers
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Towards Adversarially Robust Dataset Distillation by Curvature Regularization
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Haohan Wang
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Counter-Samples: A Stateless Strategy to Neutralize Black Box
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199
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Soften to Defend: Towards Adversarial Robustness via Self-Guided Label
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273
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243
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One Prompt Word is Enough to Boost Adversarial Robustness for
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