Detecting Adversarial Samples from Artifacts

1 March 2017

Papers citing "Detecting Adversarial Samples from Artifacts"

50 / 166 papers shown

Title
Logit Disagreement: OoD Detection with Bayesian Neural Networks Kevin Raina UQCV BDL UD PER 66 0 0 24 Feb 2025
Topological Signatures of Adversaries in Multimodal Alignments Minh Vu Geigh Zollicoffer Huy Mai B. Nebgen Boian S. Alexandrov Manish Bhattarai AAML 65 0 0 29 Jan 2025
Protego: Detecting Adversarial Examples for Vision Transformers via Intrinsic Capabilities Jialin Wu Kaikai Pan Yanjiao Chen Jiangyi Deng Shengyuan Pang Wenyuan Xu ViT AAML 48 0 0 13 Jan 2025
Adversarial Detection with a Dynamically Stable System Xiaowei Long Jie Lin Xiangyuan Yang AAML 41 0 0 11 Nov 2024
A3Rank: Augmentation Alignment Analysis for Prioritizing Overconfident Failing Samples for Deep Learning Models Zhengyuan Wei Haipeng Wang Qili Zhou William Chan 34 0 0 19 Jul 2024
HOLMES: to Detect Adversarial Examples with Multiple Detectors Jing Wen AAML 41 0 0 30 May 2024
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks Yunzhen Feng Tim G. J. Rudner Nikolaos Tsilivis Julia Kempe AAML BDL 43 1 0 27 Apr 2024
ARBiBench: Benchmarking Adversarial Robustness of Binarized Neural Networks Peng Zhao Jiehua Zhang Bowen Peng Longguang Wang Yingmei Wei Yu Liu Li Liu AAML 32 0 0 21 Dec 2023
Efficient Representation of the Activation Space in Deep Neural Networks Tanya Akumu C. Cintas G. Tadesse Adebayo Oshingbesan Skyler Speakman E. McFowland AAML 36 0 0 13 Dec 2023
Toward Stronger Textual Attack Detectors Pierre Colombo Marine Picot Nathan Noiry Guillaume Staerman Pablo Piantanida 62 5 0 21 Oct 2023
Adversarial Attacks Against Uncertainty Quantification Emanuele Ledda Daniele Angioni Giorgio Piras Giorgio Fumera Battista Biggio Fabio Roli AAML 35 2 0 19 Sep 2023
Dynamic ensemble selection based on Deep Neural Network Uncertainty Estimation for Adversarial Robustness Ruoxi Qin Linyuan Wang Xuehui Du Xing-yuan Chen Binghai Yan AAML 29 0 0 01 Aug 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
NeRFool: Uncovering the Vulnerability of Generalizable Neural Radiance Fields against Adversarial Perturbations Y. Fu Ye Yuan Souvik Kundu Shang Wu Shunyao Zhang Yingyan Lin AAML 68 6 0 10 Jun 2023
Graph-based methods coupled with specific distributional distances for adversarial attack detection dwight nwaigwe Lucrezia Carboni Martial Mermillod Sophie Achard M. Dojat AAML 32 3 0 31 May 2023
Uncertainty-based Detection of Adversarial Attacks in Semantic Segmentation Kira Maag Asja Fischer AAML UQCV 23 4 0 22 May 2023
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation Xiaowei Huang Wenjie Ruan Wei Huang Gao Jin Yizhen Dong ... Sihao Wu Peipei Xu Dengyu Wu André Freitas Mustafa A. Mustafa ALM 45 83 0 19 May 2023
Adversarial Examples Detection with Enhanced Image Difference Features based on Local Histogram Equalization Z. Yin Shaowei Zhu Han Su Jianteng Peng Wanli Lyu Bin Luo AAML 31 2 0 08 May 2023
Exploring the Connection between Robust and Generative Models Senad Beadini I. Masi AAML 32 1 0 08 Apr 2023
Detection of Uncertainty in Exceedance of Threshold (DUET): An Adversarial Patch Localizer Terence Jie Chua Wen-li Yu Junfeng Zhao AAML UQCV 24 1 0 18 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
Glaze: Protecting Artists from Style Mimicry by Text-to-Image Models Shawn Shan Jenna Cryan Emily Wenger Haitao Zheng Rana Hanocka Ben Y. Zhao WIGM 17 177 0 08 Feb 2023
Explainability and Robustness of Deep Visual Classification Models Jindong Gu AAML 47 2 0 03 Jan 2023
Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection P. Lorenz M. Keuper J. Keuper AAML 21 7 0 13 Dec 2022
Adversarial Artifact Detection in EEG-Based Brain-Computer Interfaces Xiaoqing Chen Dongrui Wu AAML 30 2 0 28 Nov 2022
Benchmarking Adversarially Robust Quantum Machine Learning at Scale Maxwell T. West S. Erfani C. Leckie M. Sevior Lloyd C. L. Hollenberg Muhammad Usman AAML OOD 30 33 0 23 Nov 2022
Improving Adversarial Robustness with Self-Paced Hard-Class Pair Reweighting Peng-Fei Hou Jie Han Xingyu Li AAML OOD 23 11 0 26 Oct 2022
ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation Fan Yin Yao Li Cho-Jui Hsieh Kai-Wei Chang AAML 69 4 0 22 Oct 2022
Robust Models are less Over-Confident Julia Grabinski Paul Gavrikov J. Keuper M. Keuper AAML 36 24 0 12 Oct 2022
Defending Against Backdoor Attack on Graph Nerual Network by Explainability B. Jiang Zhao Li AAML GNN 64 16 0 07 Sep 2022
Constraining Representations Yields Models That Know What They Don't Know João Monteiro Pau Rodríguez López Pierre-Andre Noel I. Laradji David Vazquez AAML 44 0 0 30 Aug 2022
Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps Mohammadreza Amirian Friedhelm Schwenker Thilo Stadelmann AAML 27 16 0 24 Aug 2022
Self-Ensembling Vision Transformer (SEViT) for Robust Medical Image Classification Faris Almalik Mohammad Yaqub Karthik Nandakumar ViT AAML MedIm 32 33 0 04 Aug 2022
Success of Uncertainty-Aware Deep Models Depends on Data Manifold Geometry M. Penrod Harrison Termotto Varshini Reddy Jiayu Yao Finale Doshi-Velez Weiwei Pan AAML OOD 43 1 0 02 Aug 2022
DNNShield: Dynamic Randomized Model Sparsification, A Defense Against Adversarial Machine Learning Mohammad Hossein Samavatian Saikat Majumdar Kristin Barber R. Teodorescu AAML 21 2 0 31 Jul 2022
Guiding the retraining of convolutional neural networks against adversarial inputs Francisco Durán Silverio Martínez-Fernández Michael Felderer Xavier Franch AAML 38 1 0 08 Jul 2022
Towards Realistic Semi-Supervised Learning Mamshad Nayeem Rizve Navid Kardan M. Shah 51 45 0 05 Jul 2022
Efficient Adversarial Training With Data Pruning Maximilian Kaufmann Yiren Zhao Ilia Shumailov Robert D. Mullins Nicolas Papernot AAML 42 7 0 01 Jul 2022
Detecting Adversarial Examples in Batches -- a geometrical approach Danush Kumar Venkatesh Peter Steinbach AAML 11 2 0 17 Jun 2022
Leveraging Uncertainty in Deep Learning for Pancreatic Adenocarcinoma Grading Biraja Ghoshal Bhargab Ghoshal A. Tucker UQCV MedIm 19 4 0 15 Jun 2022
Exploring Adversarial Attacks and Defenses in Vision Transformers trained with DINO Javier Rando Nasib Naimi Thomas Baumann Max Mathys AAML 20 5 0 14 Jun 2022
Detecting Textual Adversarial Examples Based on Distributional Characteristics of Data Representations Na Liu Mark Dras Wei Emma Zhang AAML 24 6 0 29 Apr 2022
A Simple Approach to Adversarial Robustness in Few-shot Image Classification Akshayvarun Subramanya Hamed Pirsiavash VLM 26 6 0 11 Apr 2022
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies Zhuang Qian Kaizhu Huang Qiufeng Wang Xu-Yao Zhang OOD AAML ObjD 54 72 0 26 Mar 2022
A Tutorial on Adversarial Learning Attacks and Countermeasures Cato Pauling Michael Gimson Muhammed Qaid Ahmad Kida Basel Halak AAML 25 11 0 21 Feb 2022
DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification A. Ćiprijanović Diana Kafkes Gregory F. Snyder F. Sánchez G. Perdue K. Pedro Brian D. Nord Sandeep Madireddy Stefan M. Wild AAML 42 15 0 28 Dec 2021
Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks Weiran Lin Keane Lucas Lujo Bauer Michael K. Reiter Mahmood Sharif AAML 31 5 0 28 Dec 2021
Explainable Deep Learning in Healthcare: A Methodological Survey from an Attribution View Di Jin Elena Sergeeva W. Weng Geeticka Chauhan Peter Szolovits OOD 39 55 0 05 Dec 2021
Medical Aegis: Robust adversarial protectors for medical images Qingsong Yao Zecheng He S. Kevin Zhou AAML MedIm 30 2 0 22 Nov 2021
Detecting AutoAttack Perturbations in the Frequency Domain P. Lorenz P. Harder Dominik Strassel M. Keuper J. Keuper AAML 19 13 0 16 Nov 2021