v1v2v3v4 (latest)

On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method

26 July 2019

Papers citing "On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method"

34 / 34 papers shown

Title
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning Sijia Liu Pin-Yu Chen B. Kailkhura Gaoyuan Zhang A. Hero III P. Varshney 72 235 0 11 Jun 2020
GeoDA: a geometric framework for black-box adversarial attacks A. Rahmati Seyed-Mohsen Moosavi-Dezfooli P. Frossard H. Dai MLAU AAML 113 120 0 13 Mar 2020
Defending against Backdoor Attack on Deep Neural Networks Kaidi Xu Sijia Liu Pin-Yu Chen Pu Zhao Xinyu Lin Xue Lin AAML 65 49 0 26 Feb 2020
Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses Tianlin Li Siyue Wang Pin-Yu Chen Yanzhi Wang Brian Kulis Xue Lin S. Chin AAML 54 42 0 20 Aug 2019
Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective Kaidi Xu Hongge Chen Sijia Liu Pin-Yu Chen Tsui-Wei Weng Mingyi Hong Xue Lin AAML 55 452 0 10 Jun 2019
Fault Sneaking Attack: a Stealthy Framework for Misleading Deep Neural Networks Pu Zhao Siyue Wang Cheng Gongye Yanzhi Wang Yunsi Fei Xinyu Lin AAML 46 76 0 28 May 2019
Defensive Quantization: When Efficiency Meets Robustness Ji Lin Chuang Gan Song Han MQ 77 203 0 17 Apr 2019
Interpreting Adversarial Examples by Activation Promotion and Suppression Kaidi Xu Sijia Liu Gaoyuan Zhang Mengshu Sun Pu Zhao Quanfu Fan Chuang Gan Xinyu Lin AAML FAtt 103 43 0 03 Apr 2019
Universal Decision-Based Black-Box Perturbations: Breaking Security-Through-Obscurity Defenses T. A. Hogan B. Kailkhura AAML 48 10 0 09 Nov 2018
Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks Siyue Wang Tianlin Li Pu Zhao Wujie Wen David Kaeli S. Chin Xinyu Lin AAML 53 70 0 13 Sep 2018
Structured Adversarial Attack: Towards General Implementation and Better Interpretability Kaidi Xu Sijia Liu Pu Zhao Pin-Yu Chen Huan Zhang Quanfu Fan Deniz Erdogmus Yanzhi Wang Xinyu Lin AAML 111 161 0 05 Aug 2018
Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors Andrew Ilyas Logan Engstrom Aleksander Madry MLAU AAML 97 375 0 20 Jul 2018
Query-Efficient Hard-label Black-box Attack:An Optimization-based Approach Minhao Cheng Thong Le Pin-Yu Chen Jinfeng Yi Huan Zhang Cho-Jui Hsieh AAML 103 348 0 12 Jul 2018
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks Chun-Chen Tu Pai-Shun Ting Pin-Yu Chen Sijia Liu Huan Zhang Jinfeng Yi Cho-Jui Hsieh Shin-Ming Cheng MLAU AAML 84 398 0 30 May 2018
Black-box Adversarial Attacks with Limited Queries and Information Andrew Ilyas Logan Engstrom Anish Athalye Jessy Lin MLAU AAML 163 1,206 0 23 Apr 2018
Query-limited Black-box Attacks to Classifiers Fnu Suya Yuan Tian David Evans Paolo Papotti AAML 43 24 0 23 Dec 2017
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models Wieland Brendel Jonas Rauber Matthias Bethge AAML 69 1,350 0 12 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
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 160 2,159 0 21 Aug 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
Robust Physical-World Attacks on Deep Learning Models Kevin Eykholt Ivan Evtimov Earlence Fernandes Yue Liu Amir Rahmati Chaowei Xiao Atul Prakash Tadayoshi Kohno Basel Alomair AAML 72 595 0 27 Jul 2017
Simple Black-Box Adversarial Perturbations for Deep Networks Nina Narodytska S. Kasiviswanathan AAML 70 240 0 19 Dec 2016
Delving into Transferable Adversarial Examples and Black-box Attacks Yanpei Liu Xinyun Chen Chang-rui Liu Basel Alomair AAML 143 1,741 0 08 Nov 2016
Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation Ilija Bogunovic Jonathan Scarlett Andreas Krause Volkan Cevher 84 91 0 24 Oct 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 268 8,583 0 16 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 545 5,910 0 08 Jul 2016
Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples Nicolas Papernot Patrick McDaniel Ian Goodfellow SILM AAML 116 1,741 0 24 May 2016
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 886 27,416 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 4,905 0 14 Nov 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,121 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 282 14,963 1 21 Dec 2013
Optimal rates for zero-order convex optimization: the power of two function evaluations John C. Duchi Michael I. Jordan Martin J. Wainwright Andre Wibisono 82 489 0 07 Dec 2013
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 369 7,957 0 13 Jun 2012
Randomized Smoothing for Stochastic Optimization John C. Duchi Peter L. Bartlett Martin J. Wainwright 104 288 0 22 Mar 2011