Practical No-box Adversarial Attacks against DNNs

Practical No-box Adversarial Attacks against DNNs

4 December 2020

Hao Chen

Papers citing "Practical No-box Adversarial Attacks against DNNs"

10 / 10 papers shown

Title
"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 31 75 0 29 Dec 2022
Multi-SpacePhish: Extending the Evasion-space of Adversarial Attacks against Phishing Website Detectors using Machine Learning Ying Yuan Giovanni Apruzzese Mauro Conti AAML 23 19 0 24 Oct 2022
Sound and Complete Verification of Polynomial Networks Elias Abad Rocamora Mehmet Fatih Şahin Fanghui Liu Grigorios G. Chrysos V. Cevher 23 5 0 15 Sep 2022
Adversarial Pixel Restoration as a Pretext Task for Transferable Perturbations H. Malik Shahina Kunhimon Muzammal Naseer Salman Khan F. Khan AAML 20 8 0 18 Jul 2022
Squeeze Training for Adversarial Robustness Qizhang Li Yiwen Guo W. Zuo Hao Chen OOD 34 9 0 23 May 2022
Practical No-box Adversarial Attacks with Training-free Hybrid Image Transformation Qilong Zhang Chaoning Zhang Chaoning Zhang Chaoqun Li Xuanhan Wang Jingkuan Song Lianli Gao AAML 30 21 0 09 Mar 2022
Training Meta-Surrogate Model for Transferable Adversarial Attack Yunxiao Qin Yuanhao Xiong Jinfeng Yi Cho-Jui Hsieh AAML 15 18 0 05 Sep 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Saeed Mian Navid Kardan M. Shah AAML 26 235 0 01 Aug 2021
Certification of embedded systems based on Machine Learning: A survey Guillaume Vidot Christophe Gabreau I. Ober Iulian Ober 11 12 0 14 Jun 2021
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 261 3,109 0 04 Nov 2016