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

1 February 2018

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

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Title
On The Relationship Between Universal Adversarial Attacks And Sparse Representations Dana Weitzner Raja Giryes AAML 32 0 0 14 Nov 2023
Intriguing Properties of Data Attribution on Diffusion Models Xiaosen Zheng Tianyu Pang Chao Du Jing Jiang Min Lin TDI 34 20 1 01 Nov 2023
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective Yifei Wang Liangchen Li Jiansheng Yang Zhouchen Lin Yisen Wang 31 11 0 30 Oct 2023
Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness Boya Zhang Weijian Luo Zhihua Zhang 34 10 0 28 Oct 2023
Toward Stronger Textual Attack Detectors Pierre Colombo Marine Picot Nathan Noiry Guillaume Staerman Pablo Piantanida 62 5 0 21 Oct 2023
On the Over-Memorization During Natural, Robust and Catastrophic Overfitting Runqi Lin Chaojian Yu Bo Han Tongliang Liu 35 7 0 13 Oct 2023
Promoting Robustness of Randomized Smoothing: Two Cost-Effective Approaches Linbo Liu T. Hoang Lam M. Nguyen Tsui-Wei Weng AAML 29 0 0 11 Oct 2023
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks Yang Wang B. Dong Ke Xu Haiyin Piao Yufei Ding Baocai Yin Xin Yang AAML 39 3 0 10 Oct 2023
A Survey of Robustness and Safety of 2D and 3D Deep Learning Models Against Adversarial Attacks Yanjie Li Bin Xie Songtao Guo Yuanyuan Yang Bin Xiao AAML 40 16 0 01 Oct 2023
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness Ambar Pal Huaijin Hao Rene Vidal 26 8 0 28 Sep 2023
Certifying LLM Safety against Adversarial Prompting Aounon Kumar Chirag Agarwal Suraj Srinivas Aaron Jiaxun Li S. Feizi Himabindu Lakkaraju AAML 27 167 0 06 Sep 2023
Robustness Analysis of Continuous-Depth Models with Lagrangian Techniques Sophie A. Neubauer Radu Grosu 20 0 0 23 Aug 2023
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds Hejia Geng Peng Li AAML 39 3 0 20 Aug 2023
Robust Mixture-of-Expert Training for Convolutional Neural Networks Yihua Zhang Ruisi Cai Tianlong Chen Guanhua Zhang Huan Zhang Pin-Yu Chen Shiyu Chang Zhangyang Wang Sijia Liu MoE AAML OOD 41 16 0 19 Aug 2023
Training on Foveated Images Improves Robustness to Adversarial Attacks Muhammad Ahmed Shah Bhiksha Raj AAML 38 4 0 01 Aug 2023
Doubly Robust Instance-Reweighted Adversarial Training Daouda Sow Sen-Fon Lin Zhangyang Wang Yitao Liang AAML OOD 33 2 0 01 Aug 2023
A LLM Assisted Exploitation of AI-Guardian Nicholas Carlini ELM SILM 24 15 0 20 Jul 2023
Enhancing Adversarial Robustness via Score-Based Optimization Boya Zhang Weijian Luo Zhihua Zhang DiffM 32 13 0 10 Jul 2023
Robust Ranking Explanations Chao Chen Chenghua Guo Guixiang Ma Ming Zeng Xi Zhang Sihong Xie FAtt AAML 35 0 0 08 Jul 2023
Group-based Robustness: A General Framework for Customized Robustness in the Real World Weiran Lin Keane Lucas Neo Eyal Lujo Bauer Michael K. Reiter Mahmood Sharif OOD AAML 42 1 0 29 Jun 2023
Adversarial Evasion Attacks Practicality in Networks: Testing the Impact of Dynamic Learning Mohamed el Shehaby Ashraf Matrawy AAML 33 7 0 08 Jun 2023
On the Importance of Backbone to the Adversarial Robustness of Object Detectors Xiao-Li Li Hang Chen Xiaolin Hu AAML 46 4 0 27 May 2023
Decoupled Kullback-Leibler Divergence Loss Jiequan Cui Zhuotao Tian Zhisheng Zhong Xiaojuan Qi Bei Yu Hanwang Zhang 39 38 0 23 May 2023
Certified Zeroth-order Black-Box Defense with Robust UNet Denoiser Astha Verma A. Subramanyam Siddhesh Bangar Naman Lal R. Shah Shiníchi Satoh 42 4 0 13 Apr 2023
On the Adversarial Inversion of Deep Biometric Representations Gioacchino Tangari Shreesh Keskar Hassan Jameel Asghar Dali Kaafar AAML 37 2 0 12 Apr 2023
Improving Fast Adversarial Training with Prior-Guided Knowledge Xiaojun Jia Yong Zhang Xingxing Wei Baoyuan Wu Ke Ma Jue Wang Xiaochun Cao AAML 37 26 0 01 Apr 2023
Generating Adversarial Samples in Mini-Batches May Be Detrimental To Adversarial Robustness T. Redgrave Colton R. Crum AAML 32 0 0 30 Mar 2023
Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness Wei Wei Jiahuan Zhou Yingying Wu AAML 15 0 0 29 Mar 2023
Provable Robustness for Streaming Models with a Sliding Window Aounon Kumar Vinu Sankar Sadasivan S. Feizi OOD AAML AI4TS 19 1 0 28 Mar 2023
Anti-DreamBooth: Protecting users from personalized text-to-image synthesis T. Le Hao Phung Thuan Hoang Nguyen Quan Dao Ngoc N. Tran Anh Tran 28 92 0 27 Mar 2023
Enhancing Multiple Reliability Measures via Nuisance-extended Information Bottleneck Jongheon Jeong Sihyun Yu Hankook Lee Jinwoo Shin AAML 44 0 0 24 Mar 2023
PIAT: Parameter Interpolation based Adversarial Training for Image Classification Kun He Xin Liu Yichen Yang Zhou Qin Weigao Wen Hui Xue J. Hopcroft AAML 30 0 0 24 Mar 2023
Generalist: Decoupling Natural and Robust Generalization Hongjun Wang Yisen Wang OOD AAML 49 14 0 24 Mar 2023
Boosting Verified Training for Robust Image Classifications via Abstraction Zhaodi Zhang Zhiyi Xue Yang Chen Si Liu Yueling Zhang Qingbin Liu Min Zhang 51 4 0 21 Mar 2023
Immune Defense: A Novel Adversarial Defense Mechanism for Preventing the Generation of Adversarial Examples Jinwei Wang Hao Wu Haihua Wang Jiawei Zhang X. Luo Bin Ma AAML 28 0 0 08 Mar 2023
Improved Robustness Against Adaptive Attacks With Ensembles and Error-Correcting Output Codes Thomas Philippon Christian Gagné AAML 28 0 0 04 Mar 2023
A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking Chang-Shu Liu Yinpeng Dong Wenzhao Xiang Xiaohu Yang Hang Su Junyi Zhu YueFeng Chen Yuan He H. Xue Shibao Zheng OOD VLM AAML 33 74 0 28 Feb 2023
Randomness in ML Defenses Helps Persistent Attackers and Hinders Evaluators Keane Lucas Matthew Jagielski Florian Tramèr Lujo Bauer Nicholas Carlini AAML 30 10 0 27 Feb 2023
Less is More: Data Pruning for Faster Adversarial Training Yize Li Pu Zhao X. Lin B. Kailkhura Ryan Goldh AAML 15 9 0 23 Feb 2023
PAD: Towards Principled Adversarial Malware Detection Against Evasion Attacks Deqiang Li Shicheng Cui Yun Li Jia Xu Fu Xiao Shouhuai Xu AAML 54 18 0 22 Feb 2023
Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples Qizhang Li Yiwen Guo W. Zuo Hao Chen AAML 39 35 0 10 Feb 2023
Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection Xilie Xu Jingfeng Zhang Feng Liu Masashi Sugiyama Mohan S. Kankanhalli AAML 26 16 0 08 Feb 2023
On the Robustness of Randomized Ensembles to Adversarial Perturbations Hassan Dbouk Naresh R Shanbhag AAML 23 7 0 02 Feb 2023
Are Defenses for Graph Neural Networks Robust? Felix Mujkanovic Simon Geisler Stephan Günnemann Aleksandar Bojchevski OOD AAML 21 56 0 31 Jan 2023
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion Zhuoqun Huang Neil G. Marchant Keane Lucas Lujo Bauer O. Ohrimenko Benjamin I. P. Rubinstein AAML 32 15 0 31 Jan 2023
Language-Driven Anchors for Zero-Shot Adversarial Robustness Xiao-Li Li Wei Emma Zhang Yining Liu Zhan Hu Bo-Wen Zhang Xiaolin Hu 34 8 0 30 Jan 2023
Improving Adversarial Transferability with Scheduled Step Size and Dual Example Zeliang Zhang Peihan Liu Xiaosen Wang Chenliang Xu AAML 37 3 0 30 Jan 2023
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing Yatong Bai Brendon G. Anderson Aerin Kim Somayeh Sojoudi AAML 36 18 0 29 Jan 2023
A Study on FGSM Adversarial Training for Neural Retrieval Simon Lupart S. Clinchant AAML 40 7 0 25 Jan 2023
A Data-Centric Approach for Improving Adversarial Training Through the Lens of Out-of-Distribution Detection Mohammad Azizmalayeri Arman Zarei Alireza Isavand M. T. Manzuri M. Rohban OODD 35 0 0 25 Jan 2023