Beware the Black-Box: on the Robustness of Recent Defenses to Adversarial Examples

18 June 2020

Papers citing "Beware the Black-Box: on the Robustness of Recent Defenses to Adversarial Examples"

8 / 8 papers shown

Title
RobustBlack: Challenging Black-Box Adversarial Attacks on State-of-the-Art Defenses Mohamed Djilani Salah Ghamizi Maxime Cordy 45 0 0 31 Dec 2024
Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness Jieren Deng Hanbin Hong A. Palmer Xin Zhou Jinbo Bi Kaleel Mahmood Yuan Hong Derek Aguiar AAML 40 0 0 25 May 2024
Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning Ethan Rathbun Kaleel Mahmood Sohaib Ahmad Caiwen Ding Marten van Dijk AAML 24 4 0 26 Nov 2022
Attacking the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples Nuo Xu Kaleel Mahmood Haowen Fang Ethan Rathbun Caiwen Ding Wujie Wen AAML 34 12 0 07 Sep 2022
On the Robustness of Vision Transformers to Adversarial Examples Kaleel Mahmood Rigel Mahmood Marten van Dijk ViT 33 218 0 31 Mar 2021
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack Minhao Cheng Simranjit Singh Patrick H. Chen Pin-Yu Chen Sijia Liu Cho-Jui Hsieh AAML 126 219 0 24 Sep 2019
ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples Xiaojun Jia Xingxing Wei Xiaochun Cao H. Foroosh AAML 69 264 0 30 Nov 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 308 5,842 0 08 Jul 2016