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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"

50 / 1,929 papers shown

Title
Detection Defenses: An Empty Promise against Adversarial Patch Attacks on Optical Flow Erik Scheurer Jenny Schmalfuss Alexander Lis Andrés Bruhn AAML 76 6 0 26 Oct 2023
Multi-scale Diffusion Denoised Smoothing Jongheon Jeong Jinwoo Shin DiffM 91 9 0 25 Oct 2023
Fast Propagation is Better: Accelerating Single-Step Adversarial Training via Sampling Subnetworks Xiaojun Jia Jianshu Li Jindong Gu Yang Bai Xiaochun Cao AAML 69 10 0 24 Oct 2023
AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models Sicheng Zhu Ruiyi Zhang Bang An Gang Wu Joe Barrow Zichao Wang Furong Huang A. Nenkova Tong Sun SILM AAML 88 49 0 23 Oct 2023
Toward Stronger Textual Attack Detectors Pierre Colombo Marine Picot Nathan Noiry Guillaume Staerman Pablo Piantanida 561 5 0 21 Oct 2023
An LLM can Fool Itself: A Prompt-Based Adversarial Attack Xilie Xu Keyi Kong Ning Liu Li-zhen Cui Di Wang Jingfeng Zhang Mohan Kankanhalli AAML SILM 126 88 0 20 Oct 2023
OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift Lin Li Yifei Wang Chawin Sitawarin Michael W. Spratling 56 4 0 19 Oct 2023
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks Yue Cao Tianlin Li Xiaofeng Cao Ivor Tsang Yang Liu Qing Guo AAML 66 2 0 18 Oct 2023
Quantifying Assistive Robustness Via the Natural-Adversarial Frontier Jerry Zhi-Yang He Zackory M. Erickson Daniel S. Brown Anca Dragan AAML 83 0 0 16 Oct 2023
On the Over-Memorization During Natural, Robust and Catastrophic Overfitting Runqi Lin Chaojian Yu Bo Han Tongliang Liu 78 9 0 13 Oct 2023
Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing Yuan Xin Dingfan Chen Michael Backes Xiao Zhang AAML 63 0 0 12 Oct 2023
Promoting Robustness of Randomized Smoothing: Two Cost-Effective Approaches Linbo Liu T. Hoang Lam M. Nguyen Tsui-Wei Weng AAML 46 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 74 3 0 10 Oct 2023
Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations Zeming Wei Yifei Wang Ang Li Yichuan Mo Yisen Wang 131 279 0 10 Oct 2023
Certification of Deep Learning Models for Medical Image Segmentation Othmane Laousy Alexandre Araujo G. Chassagnon Nikos Paragios M. Revel Maria Vakalopoulou MedIm 86 2 0 05 Oct 2023
Splitting the Difference on Adversarial Training Matan Levi A. Kontorovich 89 4 0 03 Oct 2023
Probabilistic Reach-Avoid for Bayesian Neural Networks Matthew Wicker Luca Laurenti A. Patané Nicola Paoletti Alessandro Abate Marta Z. Kwiatkowska 46 4 0 03 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 85 18 0 01 Oct 2023
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness Ambar Pal Huaijin Hao Rene Vidal 102 8 0 28 Sep 2023
Structure Invariant Transformation for better Adversarial Transferability Xiaosen Wang Zeliang Zhang Jianping Zhang AAML 76 66 0 26 Sep 2023
Projected Randomized Smoothing for Certified Adversarial Robustness Samuel Pfrommer Brendon G. Anderson Somayeh Sojoudi AAML 71 16 0 25 Sep 2023
Language Guided Adversarial Purification Himanshu Singh A. V. Subramanyam AAML 76 2 0 19 Sep 2023
Mitigating Adversarial Attacks in Federated Learning with Trusted Execution Environments Simon Queyrut V. Schiavoni Pascal Felber AAML FedML 74 10 0 13 Sep 2023
Exploring Non-additive Randomness on ViT against Query-Based Black-Box Attacks Jindong Gu Fangyun Wei Philip Torr Han Hu AAML 64 1 0 12 Sep 2023
Using Reed-Muller Codes for Classification with Rejection and Recovery Daniel Fentham David Parker Mark Ryan 45 0 0 12 Sep 2023
Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts Zhi-Yi Chin Chieh-Ming Jiang Ching-Chun Huang Pin-Yu Chen Wei-Chen Chiu DiffM 87 78 0 12 Sep 2023
Exploring Robust Features for Improving Adversarial Robustness Hong Wang Yuefan Deng Shinjae Yoo Yuewei Lin AAML 98 4 0 09 Sep 2023
Adversarially Robust Learning with Optimal Transport Regularized Divergences Jeremiah Birrell Mohammadreza Ebrahimi AAML FedML 56 0 0 07 Sep 2023
Certifying LLM Safety against Adversarial Prompting Aounon Kumar Chirag Agarwal Suraj Srinivas Aaron Jiaxun Li Soheil Feizi Himabindu Lakkaraju AAML 153 197 0 06 Sep 2023
Hindering Adversarial Attacks with Multiple Encrypted Patch Embeddings AprilPyone Maungmaung Isao Echizen Hitoshi Kiya AAML 64 2 0 04 Sep 2023
Towards Certified Probabilistic Robustness with High Accuracy Ruihan Zhang Peixin Zhang Jun Sun AAML 65 0 0 02 Sep 2023
Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models Changyu Liu Yuling Jiao Junhui Wang Jian Huang AAML 43 2 0 02 Sep 2023
Baseline Defenses for Adversarial Attacks Against Aligned Language Models Neel Jain Avi Schwarzschild Yuxin Wen Gowthami Somepalli John Kirchenbauer Ping Yeh-Chiang Micah Goldblum Aniruddha Saha Jonas Geiping Tom Goldstein AAML 176 410 0 01 Sep 2023
Image Hijacks: Adversarial Images can Control Generative Models at Runtime Luke Bailey Euan Ong Stuart J. Russell Scott Emmons VLM MLLM 93 88 0 01 Sep 2023
Intriguing Properties of Diffusion Models: An Empirical Study of the Natural Attack Capability in Text-to-Image Generative Models Takami Sato Justin Yue Nanze Chen Ningfei Wang Qi Alfred Chen DiffM 74 3 0 30 Aug 2023
Classification robustness to common optical aberrations Patrick Müller Alexander Braun Margret Keuper 68 10 0 29 Aug 2023
Advancing Adversarial Robustness Through Adversarial Logit Update Hao Xuan Peican Zhu Xingyu Li AAML 78 0 0 29 Aug 2023
DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local Smoothing Jiawei Zhang Zhongzhu Chen Huan Zhang Chaowei Xiao Yue Liu DiffM 84 26 0 28 Aug 2023
On-Manifold Projected Gradient Descent Aaron Mahler Tyrus Berry Thomas Stephens Harbir Antil Michael Merritt Jeanie Schreiber Ioannis G. Kevrekidis AAML 82 0 0 23 Aug 2023
Robustness Analysis of Continuous-Depth Models with Lagrangian Techniques Sophie A. Neubauer Radu Grosu 60 0 0 23 Aug 2023
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds Hejia Geng Peng Li AAML 146 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 91 19 0 19 Aug 2023
General Lipschitz: Certified Robustness Against Resolvable Semantic Transformations via Transformation-Dependent Randomized Smoothing Dmitrii Korzh Alireza Azadbakht Maryam Tahmasbi Alireza Javaheri AAML 81 0 0 17 Aug 2023
Symmetry Defense Against XGBoost Adversarial Perturbation Attacks Blerta Lindqvist AAML 75 0 0 10 Aug 2023
Pelta: Shielding Transformers to Mitigate Evasion Attacks in Federated Learning Simon Queyrut Yérom-David Bromberg V. Schiavoni FedML AAML 81 1 0 08 Aug 2023
A reading survey on adversarial machine learning: Adversarial attacks and their understanding Shashank Kotyan AAML 66 6 0 07 Aug 2023
FROD: Robust Object Detection for Free Muhammad Awais Awais Weiming Zhuang Zhuang Lingjuan Lingjuan Lyu Sung-Ho Sung-Ho Bae ObjD 89 1 0 03 Aug 2023
URET: Universal Robustness Evaluation Toolkit (for Evasion) Kevin Eykholt Taesung Lee D. Schales Jiyong Jang Ian Molloy Masha Zorin AAML 120 7 0 03 Aug 2023
Training on Foveated Images Improves Robustness to Adversarial Attacks Muhammad Ahmed Shah Bhiksha Raj AAML 71 4 0 01 Aug 2023
Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning Kaijie Zhu Jindong Wang Xixu Hu Xingxu Xie G. Yang AAML 74 25 0 01 Aug 2023