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Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models

12 December 2017

Wieland Brendel

Jonas Rauber

Matthias Bethge

AAML

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Papers citing "Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models"

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Title
AdvKnn: Adversarial Attacks On K-Nearest Neighbor Classifiers With Approximate Gradients Xiaodan Li YueFeng Chen Yuan He Hui Xue OOD AAML 38 9 0 15 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 127 105 0 13 Nov 2019
Learning From Brains How to Regularize Machines Zhe Li Wieland Brendel Edgar Y. Walker Erick Cobos Taliah Muhammad Jacob Reimer Matthias Bethge Fabian H. Sinz Xaq Pitkow A. Tolias OOD AAML 69 63 0 11 Nov 2019
Active Learning for Black-Box Adversarial Attacks in EEG-Based Brain-Computer Interfaces Xue Jiang Xiao Zhang Dongrui Wu AAML 76 16 0 07 Nov 2019
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 95 70 0 06 Nov 2019
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks Qiyang Li Saminul Haque Cem Anil James Lucas Roger C. Grosse Joern-Henrik Jacobsen 127 116 0 03 Nov 2019
Who is Real Bob? Adversarial Attacks on Speaker Recognition Systems Guangke Chen Sen Chen Lingling Fan Xiaoning Du Zhe Zhao Fu Song Yang Liu AAML 114 197 0 03 Nov 2019
An Alternative Surrogate Loss for PGD-based Adversarial Testing Sven Gowal J. Uesato Chongli Qin Po-Sen Huang Timothy A. Mann Pushmeet Kohli AAML 107 90 0 21 Oct 2019
A New Defense Against Adversarial Images: Turning a Weakness into a Strength Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 120 103 0 16 Oct 2019
DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural Networks Fuyuan Zhang Sankalan Pal Chowdhury M. Christakis AAML 58 8 0 14 Oct 2019
An Efficient and Margin-Approaching Zero-Confidence Adversarial Attack Yang Zhang Shiyu Chang Mo Yu Kaizhi Qian AAML 29 2 0 01 Oct 2019
Black-box Adversarial Attacks with Bayesian Optimization Satya Narayan Shukla Anit Kumar Sahu Devin Willmott J. Zico Kolter AAML MLAU 68 31 0 30 Sep 2019
Lower Bounds on Adversarial Robustness from Optimal Transport A. Bhagoji Daniel Cullina Prateek Mittal OOD OT AAML 70 94 0 26 Sep 2019
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack Minhao Cheng Simranjit Singh Patrick H. Chen Pin-Yu Chen Sijia Liu Cho-Jui Hsieh AAML 237 224 0 24 Sep 2019
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks Sekitoshi Kanai Yasutoshi Ida Yasuhiro Fujiwara Masanori Yamada S. Adachi AAML 44 1 0 19 Sep 2019
An Empirical Study towards Characterizing Deep Learning Development and Deployment across Different Frameworks and Platforms Qianyu Guo Sen Chen Xiaofei Xie Lei Ma Q. Hu Hongtao Liu Yang Liu Jianjun Zhao Xiaohong Li 94 125 0 15 Sep 2019
Sparse and Imperceivable Adversarial Attacks Francesco Croce Matthias Hein AAML 110 199 0 11 Sep 2019
Neural Belief Reasoner Haifeng Qian NAI BDL 26 1 0 10 Sep 2019
FDA: Feature Disruptive Attack Aditya Ganeshan S. VivekB. R. Venkatesh Babu AAML 118 105 0 10 Sep 2019
Adversarial Robustness Against the Union of Multiple Perturbation Models Pratyush Maini Eric Wong J. Zico Kolter OOD AAML 63 151 0 09 Sep 2019
Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information Yiren Zhao Ilia Shumailov Han Cui Xitong Gao Robert D. Mullins Ross J. Anderson AAML 82 28 0 06 Sep 2019
Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries Fnu Suya Jianfeng Chi David Evans Yuan Tian AAML 94 86 0 19 Aug 2019
On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method Pu Zhao Sijia Liu Pin-Yu Chen Nghia Hoang Kaidi Xu B. Kailkhura Xue Lin AAML 119 54 0 26 Jul 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 112 231 0 24 Jul 2019
Adversarial Security Attacks and Perturbations on Machine Learning and Deep Learning Methods Arif Siddiqi AAML 64 11 0 17 Jul 2019
Graph Interpolating Activation Improves Both Natural and Robust Accuracies in Data-Efficient Deep Learning Bao Wang Stanley J. Osher AAML AI4CE 77 10 0 16 Jul 2019
Stateful Detection of Black-Box Adversarial Attacks Steven Chen Nicholas Carlini D. Wagner AAML MLAU 69 126 0 12 Jul 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 137 493 0 03 Jul 2019
Diminishing the Effect of Adversarial Perturbations via Refining Feature Representation Nader Asadi Amirm. Sarfi Mehrdad Hosseinzadeh Sahba Tahsini M. Eftekhari AAML 32 2 0 01 Jul 2019
Accurate, reliable and fast robustness evaluation Wieland Brendel Jonas Rauber Matthias Kümmerer Ivan Ustyuzhaninov Matthias Bethge AAML OOD 94 113 0 01 Jul 2019
Defending Against Adversarial Examples with K-Nearest Neighbor Chawin Sitawarin David Wagner AAML 91 29 0 23 Jun 2019
Hiding Faces in Plain Sight: Disrupting AI Face Synthesis with Adversarial Perturbations Yuezun Li Xin Yang Baoyuan Wu Siwei Lyu AAML PICV CVBM 95 38 0 21 Jun 2019
Convergence of Adversarial Training in Overparametrized Neural Networks Ruiqi Gao Tianle Cai Haochuan Li Liwei Wang Cho-Jui Hsieh Jason D. Lee AAML 113 109 0 19 Jun 2019
The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks F. Assion Peter Schlicht Florens Greßner W. Günther Fabian Hüger Nico M. Schmidt Umair Rasheed AAML 75 14 0 17 Jun 2019
Improving Black-box Adversarial Attacks with a Transfer-based Prior Shuyu Cheng Yinpeng Dong Tianyu Pang Hang Su Jun Zhu AAML 92 274 0 17 Jun 2019
Defending Against Adversarial Attacks Using Random Forests Yifan Ding Liqiang Wang Huan Zhang Jinfeng Yi Deliang Fan Boqing Gong AAML 61 14 0 16 Jun 2019
Copy and Paste: A Simple But Effective Initialization Method for Black-Box Adversarial Attacks T. Brunner Frederik Diehl Alois Knoll AAML 44 8 0 14 Jun 2019
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks Ziang Yan Yiwen Guo Changshui Zhang AAML 79 111 0 11 Jun 2019
Robustness Verification of Tree-based Models Hongge Chen Huan Zhang Si Si Yang Li Duane S. Boning Cho-Jui Hsieh AAML 103 77 0 10 Jun 2019
On the Vulnerability of Capsule Networks to Adversarial Attacks Félix D. P. Michels Tobias Uelwer Eric Upschulte Stefan Harmeling AAML 77 24 0 09 Jun 2019
Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang Tianyun Zhang Sijia Liu Pin-Yu Chen Jiacen Xu M. Fardad Yangqiu Song AAML 72 37 0 09 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 84 62 0 08 Jun 2019
ML-LOO: Detecting Adversarial Examples with Feature Attribution Puyudi Yang Jianbo Chen Cho-Jui Hsieh Jane-ling Wang Michael I. Jordan AAML 93 101 0 08 Jun 2019
Making targeted black-box evasion attacks effective and efficient Mika Juuti B. Atli Nadarajah Asokan AAML MIACV MLAU 49 8 0 08 Jun 2019
Robustness for Non-Parametric Classification: A Generic Attack and Defense Yao-Yuan Yang Cyrus Rashtchian Yizhen Wang Kamalika Chaudhuri SILM AAML 92 43 0 07 Jun 2019
Query-efficient Meta Attack to Deep Neural Networks Jiawei Du Hu Zhang Qiufeng Wang Yi Yang Jiashi Feng AAML 66 84 0 06 Jun 2019
Multi-way Encoding for Robustness Donghyun Kim Sarah Adel Bargal Jianming Zhang Stan Sclaroff AAML 38 2 0 05 Jun 2019
Understanding the Limitations of Conditional Generative Models Ethan Fetaya J. Jacobsen Will Grathwohl R. Zemel 96 54 0 04 Jun 2019
Enhancing Transformation-based Defenses using a Distribution Classifier C. Kou H. Lee E. Chang Teck Khim Ng 67 3 0 01 Jun 2019
Functional Adversarial Attacks Cassidy Laidlaw Soheil Feizi AAML 100 185 0 29 May 2019