Detecting AutoAttack Perturbations in the Frequency Domain

Detecting AutoAttack Perturbations in the Frequency Domain

16 November 2021

Dominik Strassel

Papers citing "Detecting AutoAttack Perturbations in the Frequency Domain"

11 / 11 papers shown

Title
DFT-Based Adversarial Attack Detection in MRI Brain Imaging: Enhancing Diagnostic Accuracy in Alzheimer's Case Studies Mohammad Hossein Najafi Mohammad Morsali Mohammadmahdi Vahediahmar Saeed Bagheri Shouraki AAML MedIm 42 0 0 16 Aug 2024
FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks Hunmin Yang Jongoh Jeong Kuk-Jin Yoon AAML 57 4 0 30 Jul 2024
Prompt-Driven Contrastive Learning for Transferable Adversarial Attacks Hunmin Yang Jongoh Jeong Kuk-Jin Yoon AAML VLM 60 4 0 30 Jul 2024
Towards a Novel Perspective on Adversarial Examples Driven by Frequency Zhun Zhang Yi Zeng Qihe Liu Shijie Zhou AAML 39 0 0 16 Apr 2024
Adversarial Examples are Misaligned in Diffusion Model Manifolds P. Lorenz Ricard Durall Jansi Keuper DiffM 47 1 0 12 Jan 2024
Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection P. Lorenz M. Keuper J. Keuper AAML 16 7 0 13 Dec 2022
Robust Models are less Over-Confident Julia Grabinski Paul Gavrikov J. Keuper M. Keuper AAML 36 24 0 12 Oct 2022
Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness? P. Lorenz Dominik Strassel M. Keuper J. Keuper AAML 21 10 0 02 Dec 2021
A Frequency Perspective of Adversarial Robustness Shishira R. Maiya Max Ehrlich Vatsal Agarwal Ser-Nam Lim Tom Goldstein Abhinav Shrivastava AAML 23 38 0 26 Oct 2021
Frequency Centric Defense Mechanisms against Adversarial Examples Sanket B. Shah Param Raval Harin Khakhi M. Raval AAML 16 7 0 26 Oct 2021
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 234 677 0 19 Oct 2020