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Query complexity of adversarial attacks

2 October 2020

Papers citing "Query complexity of adversarial attacks"

36 / 36 papers shown

Title
Black-box Certification and Learning under Adversarial Perturbations H. Ashtiani Vinayak Pathak Ruth Urner AAML 50 20 0 30 Jun 2020
Constructing a provably adversarially-robust classifier from a high accuracy one Grzegorz Gluch R. Urbanke AAML 42 2 0 16 Dec 2019
On the Hardness of Robust Classification Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell 44 43 0 12 Sep 2019
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers Hadi Salman Greg Yang Jungshian Li Pengchuan Zhang Huan Zhang Ilya P. Razenshteyn Sébastien Bubeck AAML 71 551 0 09 Jun 2019
VC Classes are Adversarially Robustly Learnable, but Only Improperly Omar Montasser Steve Hanneke Nathan Srebro 43 140 0 12 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 152 2,044 0 08 Feb 2019
Adversarial Examples from Cryptographic Pseudo-Random Generators Sébastien Bubeck Y. Lee Eric Price Ilya P. Razenshteyn AAML 60 33 0 15 Nov 2018
Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution Dimitrios I. Diochnos Saeed Mahloujifar Mohammad Mahmoody AAML 41 72 0 29 Oct 2018
Rademacher Complexity for Adversarially Robust Generalization Dong Yin Kannan Ramchandran Peter L. Bartlett AAML 90 260 0 29 Oct 2018
Adversarial Attacks and Defences: A Survey Anirban Chakraborty Manaar Alam Vishal Dey Anupam Chattopadhyay Debdeep Mukhopadhyay AAML OOD 78 679 0 28 Sep 2018
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability Kai Y. Xiao Vincent Tjeng Nur Muhammad (Mahi) Shafiullah Aleksander Madry AAML OOD 41 201 0 09 Sep 2018
Distributionally Adversarial Attack T. Zheng Changyou Chen K. Ren OOD 80 121 0 16 Aug 2018
PAC-learning in the presence of evasion adversaries Daniel Cullina A. Bhagoji Prateek Mittal AAML 60 54 0 05 Jun 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 104 1,781 0 30 May 2018
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 119 233 0 25 May 2018
Adversarially Robust Generalization Requires More Data Ludwig Schmidt Shibani Santurkar Dimitris Tsipras Kunal Talwar Aleksander Madry OOD AAML 146 790 0 30 Apr 2018
Black-box Adversarial Attacks with Limited Queries and Information Andrew Ilyas Logan Engstrom Anish Athalye Jessy Lin MLAU AAML 163 1,200 0 23 Apr 2018
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks J. Uesato Brendan O'Donoghue Aaron van den Oord Pushmeet Kohli AAML 152 604 0 15 Feb 2018
Certified Robustness to Adversarial Examples with Differential Privacy Mathias Lécuyer Vaggelis Atlidakis Roxana Geambasu Daniel J. Hsu Suman Jana SILM AAML 96 934 0 09 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 226 3,186 0 01 Feb 2018
Generating Adversarial Examples with Adversarial Networks Chaowei Xiao Yue Liu Jun-Yan Zhu Warren He M. Liu Basel Alomair GAN AAML 115 899 0 08 Jan 2018
The Robust Manifold Defense: Adversarial Training using Generative Models A. Jalal Andrew Ilyas C. Daskalakis A. Dimakis AAML 64 174 0 26 Dec 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 157 2,153 0 21 Aug 2017
Learning Universal Adversarial Perturbations with Generative Models Jamie Hayes G. Danezis AAML 63 54 0 17 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 80 1,882 0 14 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 307 12,069 0 19 Jun 2017
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples Yizhen Wang S. Jha Kamalika Chaudhuri AAML 181 155 0 13 Jun 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 126 1,864 0 20 May 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 177 2,725 0 19 May 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks Weilin Xu David Evans Yanjun Qi AAML 85 1,269 0 04 Apr 2017
Delving into Transferable Adversarial Examples and Black-box Attacks Yanpei Liu Xinyun Chen Chang-rui Liu Basel Alomair AAML 140 1,737 0 08 Nov 2016
Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples Nicolas Papernot Patrick McDaniel Ian Goodfellow SILM AAML 114 1,739 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 3,678 0 08 Feb 2016
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 169 3,271 0 05 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 275 14,927 1 21 Dec 2013