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Towards Deep Learning Models Resistant to Adversarial Attacks

19 June 2017

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Papers citing "Towards Deep Learning Models Resistant to Adversarial Attacks"

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Title
A Geometric Perspective on the Transferability of Adversarial Directions Duncan C. McElfresh H. Bidkhori Dimitris Papailiopoulos AAML 50 17 0 08 Nov 2018
AdVersarial: Perceptual Ad Blocking meets Adversarial Machine Learning K. Makarychev Pascal Dupré Yury Makarychev Giancarlo Pellegrino Dan Boneh AAML 104 64 0 08 Nov 2018
MixTrain: Scalable Training of Verifiably Robust Neural Networks Yue Zhang Yizheng Chen Ahmed Abdou Mohsen Guizani AAML 43 23 0 06 Nov 2018
SparseFool: a few pixels make a big difference Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 72 200 0 06 Nov 2018
Learning to Defend by Learning to Attack Haoming Jiang Zhehui Chen Yuyang Shi Bo Dai T. Zhao 108 22 0 03 Nov 2018
Semidefinite relaxations for certifying robustness to adversarial examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 124 439 0 02 Nov 2018
Efficient Neural Network Robustness Certification with General Activation Functions Huan Zhang Tsui-Wei Weng Pin-Yu Chen Cho-Jui Hsieh Luca Daniel AAML 124 765 0 02 Nov 2018
Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks Davide Maiorca Battista Biggio Giorgio Giacinto AAML 80 47 0 02 Nov 2018
Stronger Data Poisoning Attacks Break Data Sanitization Defenses Pang Wei Koh Jacob Steinhardt Percy Liang 110 244 0 02 Nov 2018
Spectral Signatures in Backdoor Attacks Brandon Tran Jerry Li Aleksander Madry AAML 106 800 0 01 Nov 2018
Improving Adversarial Robustness by Encouraging Discriminative Features Chirag Agarwal Anh Totti Nguyen Dan Schonfeld OOD 66 5 0 01 Nov 2018
On the Geometry of Adversarial Examples Marc Khoury Dylan Hadfield-Menell AAML 81 79 0 01 Nov 2018
Excessive Invariance Causes Adversarial Vulnerability J. Jacobsen Jens Behrmann R. Zemel Matthias Bethge AAML 127 167 0 01 Nov 2018
On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models Sven Gowal Krishnamurthy Dvijotham Robert Stanforth Rudy Bunel Chongli Qin J. Uesato Relja Arandjelović Timothy A. Mann Pushmeet Kohli AAML 109 559 0 30 Oct 2018
Improved Network Robustness with Adversary Critic Alexander Matyasko Lap-Pui Chau AAML 50 14 0 30 Oct 2018
Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution Dimitrios I. Diochnos Saeed Mahloujifar Mohammad Mahmoody AAML 58 72 0 29 Oct 2018
Logit Pairing Methods Can Fool Gradient-Based Attacks Marius Mosbach Maksym Andriushchenko T. A. Trost Matthias Hein Dietrich Klakow AAML 68 83 0 29 Oct 2018
Rademacher Complexity for Adversarially Robust Generalization Dong Yin Kannan Ramchandran Peter L. Bartlett AAML 107 261 0 29 Oct 2018
RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications Huan Zhang Pengchuan Zhang Cho-Jui Hsieh AAML 72 63 0 28 Oct 2018
Evading classifiers in discrete domains with provable optimality guarantees B. Kulynych Jamie Hayes N. Samarin Carmela Troncoso AAML 85 20 0 25 Oct 2018
Attack Graph Convolutional Networks by Adding Fake Nodes Xiaoyun Wang Minhao Cheng Joe Eaton Cho-Jui Hsieh S. F. Wu AAML GNN 118 78 0 25 Oct 2018
Robust Adversarial Learning via Sparsifying Front Ends S. Gopalakrishnan Zhinus Marzi Metehan Cekic Upamanyu Madhow Ramtin Pedarsani AAML 58 3 0 24 Oct 2018
Interpreting Black Box Predictions using Fisher Kernels Rajiv Khanna Been Kim Joydeep Ghosh Oluwasanmi Koyejo FAtt 91 104 0 23 Oct 2018
Stochastic Substitute Training: A Gray-box Approach to Craft Adversarial Examples Against Gradient Obfuscation Defenses Mohammad J. Hashemi Greg Cusack Eric Keller AAML SILM 51 8 0 23 Oct 2018
Sparse DNNs with Improved Adversarial Robustness Yiwen Guo Chao Zhang Changshui Zhang Yurong Chen AAML 100 154 0 23 Oct 2018
Adversarial Risk Bounds via Function Transformation Justin Khim Po-Ling Loh AAML 90 50 0 22 Oct 2018
Provable Robustness of ReLU networks via Maximization of Linear Regions Francesco Croce Maksym Andriushchenko Matthias Hein 92 166 0 17 Oct 2018
Security Matters: A Survey on Adversarial Machine Learning Guofu Li Pengjia Zhu Jin Li Zhemin Yang Ning Cao Zhiyi Chen AAML 90 25 0 16 Oct 2018
Concise Explanations of Neural Networks using Adversarial Training P. Chalasani Jiefeng Chen Aravind Sadagopan S. Jha Xi Wu AAML FAtt 172 13 0 15 Oct 2018
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation Chaowei Xiao Ruizhi Deng Yue Liu Feng Yu M. Liu Basel Alomair AAML 59 99 0 11 Oct 2018
Is PGD-Adversarial Training Necessary? Alternative Training via a Soft-Quantization Network with Noisy-Natural Samples Only T. Zheng Changyou Chen K. Ren AAML 57 6 0 10 Oct 2018
Average Margin Regularization for Classifiers Matt Olfat A. Aswani OOD AAML 23 1 0 09 Oct 2018
Efficient Two-Step Adversarial Defense for Deep Neural Networks Ting-Jui Chang Yukun He Peng Li AAML 69 11 0 08 Oct 2018
Combinatorial Attacks on Binarized Neural Networks Elias Boutros Khalil Amrita Gupta B. Dilkina AAML 89 40 0 08 Oct 2018
Feature Prioritization and Regularization Improve Standard Accuracy and Adversarial Robustness Chihuang Liu Joseph Jaja AAML 67 12 0 04 Oct 2018
Improved Generalization Bounds for Adversarially Robust Learning Idan Attias A. Kontorovich Yishay Mansour 82 20 0 04 Oct 2018
Weakly-Convex Concave Min-Max Optimization: Provable Algorithms and Applications in Machine Learning Hassan Rafique Mingrui Liu Qihang Lin Tianbao Yang 126 111 0 04 Oct 2018
Can Adversarially Robust Learning Leverage Computational Hardness? Saeed Mahloujifar Mohammad Mahmoody AAML OOD 74 48 0 02 Oct 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon A. Serban E. Poll Joost Visser SILM AAML 102 49 0 02 Oct 2018
Improved robustness to adversarial examples using Lipschitz regularization of the loss Chris Finlay Adam M. Oberman B. Abbasi 80 34 0 01 Oct 2018
Improving the Generalization of Adversarial Training with Domain Adaptation Chuanbiao Song Kun He Liwei Wang John E. Hopcroft AAML OOD 112 132 0 01 Oct 2018
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network Xuanqing Liu Yao Li Chongruo Wu Cho-Jui Hsieh AAML OOD 93 171 0 01 Oct 2018
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks Kenneth T. Co Luis Muñoz-González Sixte de Maupeou Emil C. Lupu AAML 74 67 0 30 Sep 2018
A Kernel Perspective for Regularizing Deep Neural Networks A. Bietti Grégoire Mialon Dexiong Chen Julien Mairal 82 15 0 30 Sep 2018
CAAD 2018: Generating Transferable Adversarial Examples Yash Sharma Tien-Dung Le M. Alzantot AAML SILM 85 7 0 29 Sep 2018
Interpreting Adversarial Robustness: A View from Decision Surface in Input Space Fuxun Yu Chenchen Liu Yanzhi Wang Liang Zhao Xiang Chen AAML OOD 90 27 0 29 Sep 2018
Counterfactual Fairness in Text Classification through Robustness Sahaj Garg Vincent Perot Nicole Limtiaco Ankur Taly Ed H. Chi Alex Beutel 102 261 0 27 Sep 2018
Neural Networks with Structural Resistance to Adversarial Attacks Luca de Alfaro AAML 45 5 0 25 Sep 2018
Fast Geometrically-Perturbed Adversarial Faces Ali Dabouei Sobhan Soleymani J. Dawson Nasser M. Nasrabadi CVBM AAML 64 65 0 24 Sep 2018
On The Utility of Conditional Generation Based Mutual Information for Characterizing Adversarial Subspaces Chia-Yi Hsu Pei-Hsuan Lu Pin-Yu Chen Chia-Mu Yu AAML 70 1 0 24 Sep 2018