v1v2 (latest)

Motivating the Rules of the Game for Adversarial Example Research

18 July 2018

Justin Gilmer

Papers citing "Motivating the Rules of the Game for Adversarial Example Research"

36 / 86 papers shown

Title
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 131 1,864 0 20 May 2017
MTDeep: Boosting the Security of Deep Neural Nets Against Adversarial Attacks with Moving Target Defense Sailik Sengupta Tathagata Chakraborti S. Kambhampati AAML 100 63 0 19 May 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 177 2,728 0 19 May 2017
Generative Adversarial Trainer: Defense to Adversarial Perturbations with GAN Hyeungill Lee Sungyeob Han Jungwoo Lee AAML GAN 42 149 0 09 May 2017
Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression Nilaksh Das Madhuri Shanbhogue Shang-Tse Chen Fred Hohman Li-Wei Chen Michael E. Kounavis Duen Horng Chau AAML 64 307 0 08 May 2017
Parseval Networks: Improving Robustness to Adversarial Examples Moustapha Cissé Piotr Bojanowski Edouard Grave Yann N. Dauphin Nicolas Usunier AAML 138 808 0 28 Apr 2017
Enhancing Robustness of Machine Learning Systems via Data Transformations A. Bhagoji Daniel Cullina Chawin Sitawarin Prateek Mittal AAML 50 231 0 09 Apr 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks Weilin Xu David Evans Yanjun Qi AAML 87 1,271 0 04 Apr 2017
SafetyNet: Detecting and Rejecting Adversarial Examples Robustly Jiajun Lu Theerasit Issaranon David A. Forsyth GAN 90 381 0 01 Apr 2017
Biologically inspired protection of deep networks from adversarial attacks Aran Nayebi Surya Ganguli AAML 71 115 0 27 Mar 2017
On the Limitation of Convolutional Neural Networks in Recognizing Negative Images Hossein Hosseini Baicen Xiao Mayoore S. Jaiswal Radha Poovendran 58 123 0 20 Mar 2017
Detecting Adversarial Samples from Artifacts Reuben Feinman Ryan R. Curtin S. Shintre Andrew B. Gardner AAML 93 894 0 01 Mar 2017
Robustness to Adversarial Examples through an Ensemble of Specialists Mahdieh Abbasi Christian Gagné AAML 79 109 0 22 Feb 2017
DeepCloak: Masking Deep Neural Network Models for Robustness Against Adversarial Samples Ji Gao Beilun Wang Zeming Lin Weilin Xu Yanjun Qi AAML 49 89 0 22 Feb 2017
On the (Statistical) Detection of Adversarial Examples Kathrin Grosse Praveen Manoharan Nicolas Papernot Michael Backes Patrick McDaniel AAML 76 714 0 21 Feb 2017
On Detecting Adversarial Perturbations J. H. Metzen Tim Genewein Volker Fischer Bastian Bischoff AAML 61 950 0 14 Feb 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 318 1,873 0 03 Feb 2017
Dense Associative Memory is Robust to Adversarial Inputs Dmitry Krotov J. Hopfield AAML 67 112 0 04 Jan 2017
Adversarial Examples Detection in Deep Networks with Convolutional Filter Statistics Xin Li Fuxin Li GAN AAML 110 365 0 22 Dec 2016
Adversary Resistant Deep Neural Networks with an Application to Malware Detection Qinglong Wang Wenbo Guo Kaixuan Zhang Alexander Ororbia Masashi Sugiyama C. Lee Giles Xue Liu AAML 57 175 0 05 Oct 2016
Robustness of classifiers: from adversarial to random noise Alhussein Fawzi Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 92 376 0 31 Aug 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 266 8,579 0 16 Aug 2016
A study of the effect of JPG compression on adversarial images Gintare Karolina Dziugaite Zoubin Ghahramani Daniel M. Roy AAML 86 534 0 02 Aug 2016
Early Methods for Detecting Adversarial Images Dan Hendrycks Kevin Gimpel AAML 77 236 0 01 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 545 5,909 0 08 Jul 2016
Adversarial Perturbations Against Deep Neural Networks for Malware Classification Kathrin Grosse Nicolas Papernot Praveen Manoharan Michael Backes Patrick McDaniel AAML 64 418 0 14 Jun 2016
Measuring Neural Net Robustness with Constraints Osbert Bastani Yani Andrew Ioannou Leonidas Lampropoulos Dimitrios Vytiniotis A. Nori A. Criminisi AAML 89 424 0 24 May 2016
Suppressing the Unusual: towards Robust CNNs using Symmetric Activation Functions Qiyang Zhao Lewis D. Griffin AAML 44 28 0 16 Mar 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 112 3,966 0 24 Nov 2015
Foveation-based Mechanisms Alleviate Adversarial Examples Yan Luo Xavier Boix Gemma Roig T. Poggio Qi Zhao AAML 67 170 0 19 Nov 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks Nicolas Papernot Patrick McDaniel Xi Wu S. Jha A. Swami AAML 113 3,077 0 14 Nov 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 280 19,107 0 20 Dec 2014
Towards Deep Neural Network Architectures Robust to Adversarial Examples S. Gu Luca Rigazio AAML 76 844 0 11 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 171 3,275 0 05 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 277 14,961 1 21 Dec 2013
Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks Ian Goodfellow Yaroslav Bulatov Julian Ibarz Sacha Arnoud Vinay D. Shet 113 720 0 20 Dec 2013