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Provable defenses against adversarial examples via the convex outer adversarial polytope

2 November 2017

Eric Wong

J. Zico Kolter

AAML

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Papers citing "Provable defenses against adversarial examples via the convex outer adversarial polytope"

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Title
PROVEN: Certifying Robustness of Neural Networks with a Probabilistic Approach Tsui-Wei Weng Pin-Yu Chen Lam M. Nguyen M. Squillante Ivan Oseledets Luca Daniel AAML 77 30 0 18 Dec 2018
A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability Xiaowei Huang Daniel Kroening Wenjie Ruan Marta Kwiatkowska Youcheng Sun Emese Thamo Min Wu Xinping Yi AAML 130 51 0 18 Dec 2018
Designing Adversarially Resilient Classifiers using Resilient Feature Engineering Kevin Eykholt A. Prakash AAML 57 4 0 17 Dec 2018
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 187 559 0 13 Dec 2018
On the Security of Randomized Defenses Against Adversarial Samples K. Sharad G. Marson H. Truong Ghassan O. Karame AAML 47 1 0 11 Dec 2018
Adversarial Attacks, Regression, and Numerical Stability Regularization A. Nguyen Edward Raff AAML 44 30 0 07 Dec 2018
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks Akhilan Boopathy Tsui-Wei Weng Pin-Yu Chen Sijia Liu Luca Daniel AAML 158 138 0 29 Nov 2018
A randomized gradient-free attack on ReLU networks Francesco Croce Matthias Hein AAML 74 21 0 28 Nov 2018
Strong mixed-integer programming formulations for trained neural networks Ross Anderson Joey Huchette Christian Tjandraatmadja J. Vielma 187 259 0 20 Nov 2018
Lightweight Lipschitz Margin Training for Certified Defense against Adversarial Examples Hajime Ono Tsubasa Takahashi Kazuya Kakizaki AAML 49 4 0 20 Nov 2018
A Statistical Approach to Assessing Neural Network Robustness Stefan Webb Tom Rainforth Yee Whye Teh M. P. Kumar AAML 72 83 0 17 Nov 2018
nn-dependability-kit: Engineering Neural Networks for Safety-Critical Autonomous Driving Systems Chih-Hong Cheng Chung-Hao Huang Georg Nührenberg 57 11 0 16 Nov 2018
A Spectral View of Adversarially Robust Features Shivam Garg Vatsal Sharan B. Zhang Gregory Valiant AAML 151 21 0 15 Nov 2018
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 72 68 0 13 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
Semidefinite relaxations for certifying robustness to adversarial examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 111 439 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
Stronger Data Poisoning Attacks Break Data Sanitization Defenses Pang Wei Koh Jacob Steinhardt Percy Liang 108 244 0 02 Nov 2018
On the Geometry of Adversarial Examples Marc Khoury Dylan Hadfield-Menell AAML 79 79 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 107 559 0 30 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 105 261 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 68 63 0 28 Oct 2018
Towards Robust Deep Neural Networks Timothy E. Wang Jack Gu D. Mehta Xiaojun Zhao Edgar A. Bernal OOD 90 11 0 27 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
Adversarial Risk Bounds via Function Transformation Justin Khim Po-Ling Loh AAML 90 50 0 22 Oct 2018
Cost-Sensitive Robustness against Adversarial Examples Xiao Zhang David Evans AAML 76 26 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
Combinatorial Attacks on Binarized Neural Networks Elias Boutros Khalil Amrita Gupta B. Dilkina AAML 89 40 0 08 Oct 2018
Empirical Bounds on Linear Regions of Deep Rectifier Networks Thiago Serra Srikumar Ramalingam 76 42 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
Verification for Machine Learning, Autonomy, and Neural Networks Survey Weiming Xiang Patrick Musau A. Wild Diego Manzanas Lopez Nathaniel P. Hamilton Xiaodong Yang Joel A. Rosenfeld Taylor T. Johnson 88 102 0 03 Oct 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon A. Serban E. Poll Joost Visser SILM AAML 102 49 0 02 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
A Kernel Perspective for Regularizing Deep Neural Networks A. Bietti Grégoire Mialon Dexiong Chen Julien Mairal 82 15 0 30 Sep 2018
Efficient Formal Safety Analysis of Neural Networks Shiqi Wang Kexin Pei Justin Whitehouse Junfeng Yang Suman Jana AAML 81 406 0 19 Sep 2018
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions Yusuke Tsuzuku Issei Sato AAML 82 62 0 11 Sep 2018
Certified Adversarial Robustness with Additive Noise Bai Li Changyou Chen Wenlin Wang Lawrence Carin AAML 117 350 0 10 Sep 2018
The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure Saeed Mahloujifar Dimitrios I. Diochnos Mohammad Mahmoody 72 152 0 09 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 61 202 0 09 Sep 2018
Are adversarial examples inevitable? Ali Shafahi Wenjie Huang Christoph Studer Soheil Feizi Tom Goldstein SILM 88 283 0 06 Sep 2018
Lipschitz Networks and Distributional Robustness Zac Cranko Simon Kornblith Zhan Shi Richard Nock OOD 63 11 0 04 Sep 2018
Distributionally Adversarial Attack T. Zheng Changyou Chen K. Ren OOD 101 123 0 16 Aug 2018
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
Limitations of the Lipschitz constant as a defense against adversarial examples Todd P. Huster C. Chiang R. Chadha AAML 57 84 0 25 Jul 2018
Attack and defence in cellular decision-making: lessons from machine learning Thomas J. Rademaker Emmanuel Bengio P. Franccois AAML 49 4 0 10 Jul 2018
A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees Min Wu Matthew Wicker Wenjie Ruan Xiaowei Huang Marta Kwiatkowska AAML 91 111 0 10 Jul 2018
Adversarial Reprogramming of Neural Networks Gamaleldin F. Elsayed Ian Goodfellow Jascha Narain Sohl-Dickstein OOD AAML 55 183 0 28 Jun 2018
On the Robustness of Interpretability Methods David Alvarez-Melis Tommi Jaakkola 118 529 0 21 Jun 2018