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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"

23 / 423 papers shown

Title
Security and Privacy Issues in Deep Learning Ho Bae Jaehee Jang Dahuin Jung Hyemi Jang Heonseok Ha Hyungyu Lee Sungroh Yoon SILM MIACV 143 79 0 31 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 112 348 0 12 Jul 2018
Vulnerability Analysis of Chest X-Ray Image Classification Against Adversarial Attacks Saeid Asgari Taghanaki A. Das Ghassan Hamarneh MedIm 91 52 0 09 Jul 2018
Adversarial Robustness Toolbox v1.0.0 Maria-Irina Nicolae M. Sinn Minh-Ngoc Tran Beat Buesser Ambrish Rawat ... Nathalie Baracaldo Bryant Chen Heiko Ludwig Ian Molloy Ben Edwards AAML VLM 91 462 0 03 Jul 2018
DeepLaser: Practical Fault Attack on Deep Neural Networks J. Breier Xiaolu Hou Dirmanto Jap Lei Ma S. Bhasin Yang Liu AAML AI4CE 80 19 0 15 Jun 2018
Hierarchical interpretations for neural network predictions Chandan Singh W. James Murdoch Bin Yu 84 146 0 14 Jun 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 88 399 0 30 May 2018
GenAttack: Practical Black-box Attacks with Gradient-Free Optimization M. Alzantot Yash Sharma Supriyo Chakraborty Huan Zhang Cho-Jui Hsieh Mani B. Srivastava AAML 100 258 0 28 May 2018
Towards the first adversarially robust neural network model on MNIST Lukas Schott Jonas Rauber Matthias Bethge Wieland Brendel AAML OOD 75 370 0 23 May 2018
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing Jingyi Wang Jun Sun Peixin Zhang Xinyu Wang AAML 76 41 0 14 May 2018
Query-Efficient Black-Box Attack Against Sequence-Based Malware Classifiers Ishai Rosenberg A. Shabtai Yuval Elovici Lior Rokach AAML 75 10 0 23 Apr 2018
Black-box Adversarial Attacks with Limited Queries and Information Andrew Ilyas Logan Engstrom Anish Athalye Jessy Lin MLAU AAML 184 1,208 0 23 Apr 2018
Adversarial Attacks and Defences Competition Alexey Kurakin Ian Goodfellow Samy Bengio Yinpeng Dong Fangzhou Liao ... Junjiajia Long Yerkebulan Berdibekov Takuya Akiba Seiya Tokui Motoki Abe AAML SILM 95 322 0 31 Mar 2018
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems Lei Ma Felix Juefei Xu Fuyuan Zhang Jiyuan Sun Minhui Xue ... Ting Su Li Li Yang Liu Jianjun Zhao Yadong Wang ELM 80 626 0 20 Mar 2018
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples Minhao Cheng Jinfeng Yi Pin-Yu Chen Huan Zhang Cho-Jui Hsieh SILM AAML 116 245 0 03 Mar 2018
Understanding and Enhancing the Transferability of Adversarial Examples Lei Wu Zhanxing Zhu Cheng Tai E. Weinan AAML SILM 77 99 0 27 Feb 2018
Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples Jake Zhao Kyunghyun Cho AAML 160 20 0 26 Feb 2018
Divide, Denoise, and Defend against Adversarial Attacks Seyed-Mohsen Moosavi-Dezfooli A. Shrivastava Oncel Tuzel AAML 57 45 0 19 Feb 2018
Are Generative Classifiers More Robust to Adversarial Attacks? Yingzhen Li John Bradshaw Yash Sharma AAML 102 79 0 19 Feb 2018
DARTS: Deceiving Autonomous Cars with Toxic Signs Chawin Sitawarin A. Bhagoji Arsalan Mosenia M. Chiang Prateek Mittal AAML 117 236 0 18 Feb 2018
Anomaly Detection using One-Class Neural Networks Raghavendra Chalapathy A. Menon Sanjay Chawla UQCV 77 399 0 18 Feb 2018
Foolbox: A Python toolbox to benchmark the robustness of machine learning models Jonas Rauber Wieland Brendel Matthias Bethge AAML 82 283 0 13 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 339 12,166 0 19 Jun 2017