A critique of the DeepSec Platform for Security Analysis of Deep Learning Models

17 May 2019

Papers citing "A critique of the DeepSec Platform for Security Analysis of Deep Learning Models"

7 / 7 papers shown

Title
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples Antonio Emanuele Cinà Jérôme Rony Maura Pintor Christian Scano Ambra Demontis Battista Biggio Ismail Ben Ayed Fabio Roli ELM AAML SILM 46 8 0 30 Apr 2024
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice Giovanni Apruzzese Hyrum S. Anderson Savino Dambra D. Freeman Fabio Pierazzi Kevin A. Roundy AAML 38 75 0 29 Dec 2022
Can Adversarial Training Be Manipulated By Non-Robust Features? Lue Tao Lei Feng Hongxin Wei Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 139 16 0 31 Jan 2022
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 234 681 0 19 Oct 2020
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 31 36 0 26 Dec 2019
Taking Care of The Discretization Problem: A Comprehensive Study of the Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer Domain Lei Bu Yuchao Duan Fu Song Zhe Zhao AAML 37 18 0 19 May 2019
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 335 5,849 0 08 Jul 2016