A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks

10 October 2023

Yang Wang

Xin Yang

Papers citing "A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks"

23 / 23 papers shown

Title
Biologically Inspired Dynamic Thresholds for Spiking Neural Networks Jianchuan Ding B. Dong Felix Heide Yufei Ding Yunduo Zhou Baocai Yin Xin Yang 40 24 0 09 Jun 2022
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 138 1,181 0 12 Jan 2020
ROSA: Robust Salient Object Detection against Adversarial Attacks Haofeng Li Guanbin Li Yizhou Yu AAML 56 28 0 09 May 2019
Efficient Decision-based Black-box Adversarial Attacks on Face Recognition Yinpeng Dong Hang Su Baoyuan Wu Zhifeng Li Wen Liu Tong Zhang Jun Zhu CVBM AAML 77 408 0 09 Apr 2019
Improving Adversarial Robustness via Promoting Ensemble Diversity Tianyu Pang Kun Xu Chao Du Ning Chen Jun Zhu AAML 83 439 0 25 Jan 2019
Towards Fast Computation of Certified Robustness for ReLU Networks Tsui-Wei Weng Huan Zhang Hongge Chen Zhao Song Cho-Jui Hsieh Duane S. Boning Inderjit S. Dhillon Luca Daniel AAML 108 695 0 25 Apr 2018
Improving Transferability of Adversarial Examples with Input Diversity Cihang Xie Zhishuai Zhang Yuyin Zhou Song Bai Jianyu Wang Zhou Ren Alan Yuille AAML 106 1,125 0 19 Mar 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 243 3,194 0 01 Feb 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng Huan Zhang Pin-Yu Chen Jinfeng Yi D. Su Yupeng Gao Cho-Jui Hsieh Luca Daniel AAML 83 468 0 31 Jan 2018
Towards Robust Neural Networks via Random Self-ensemble Xuanqing Liu Minhao Cheng Huan Zhang Cho-Jui Hsieh FedML AAML 97 422 0 02 Dec 2017
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples Pin-Yu Chen Yash Sharma Huan Zhang Jinfeng Yi Cho-Jui Hsieh AAML 66 641 0 13 Sep 2017
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models Pin-Yu Chen Huan Zhang Yash Sharma Jinfeng Yi Cho-Jui Hsieh AAML 85 1,885 0 14 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 315 12,117 0 19 Jun 2017
Extending Defensive Distillation Nicolas Papernot Patrick McDaniel AAML 67 119 0 15 May 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 318 1,874 0 03 Feb 2017
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 266 8,579 0 16 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 545 5,909 0 08 Jul 2016
Measuring Neural Net Robustness with Constraints Osbert Bastani Yani Andrew Ioannou Leonidas Lampropoulos Dimitrios Vytiniotis A. Nori A. Criminisi AAML 89 424 0 24 May 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 75 3,682 0 08 Feb 2016
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 886 27,412 0 02 Dec 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 154 4,903 0 14 Nov 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 280 19,107 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 280 14,961 1 21 Dec 2013