On the Limitations of Stochastic Pre-processing Defenses

On the Limitations of Stochastic Pre-processing Defenses

19 June 2022

Nicolas Papernot

Papers citing "On the Limitations of Stochastic Pre-processing Defenses"

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Title
SEA: Shareable and Explainable Attribution for Query-based Black-box Attacks Yue Gao Ilia Shumailov Kassem Fawaz AAML 145 0 0 21 Feb 2025
ADBM: Adversarial diffusion bridge model for reliable adversarial purification Xiao-Li Li Wenxuan Sun Huanran Chen Qiongxiu Li Yining Liu Yingzhe He Jie Shi Xiaolin Hu AAML 58 7 0 01 Aug 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
Randomness in ML Defenses Helps Persistent Attackers and Hinders Evaluators Keane Lucas Matthew Jagielski Florian Tramèr Lujo Bauer Nicholas Carlini AAML 30 9 0 27 Feb 2023
Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition Luke E. Richards Edward Raff Cynthia Matuszek AAML 16 2 0 17 Feb 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 24 208 0 09 Feb 2023
Re-purposing Perceptual Hashing based Client Side Scanning for Physical Surveillance Ashish Hooda Andrey Labunets Tadayoshi Kohno Earlence Fernandes 11 2 0 08 Dec 2022
Diffusion Models for Adversarial Purification Weili Nie Brandon Guo Yujia Huang Chaowei Xiao Arash Vahdat Anima Anandkumar WIGM 212 418 0 16 May 2022
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 35 4 0 16 Sep 2021
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,198 0 01 Sep 2014