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Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction

23 May 2017

Papers citing "Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction"

37 / 37 papers shown

Title
Improving the Transferability of Adversarial Examples by Inverse Knowledge Distillation Wenyuan Wu Zheng Liu Yong Chen Chao Su Dezhong Peng Xu Wang AAML 184 0 0 24 Feb 2025
2DSig-Detect: a semi-supervised framework for anomaly detection on image data using 2D-signatures Xinheng Xie Kureha Yamaguchi Margaux Leblanc Simon Malzard Varun Chhabra Victoria Nockles Yue-bo Wu AAML 219 1 0 08 Sep 2024
Leveraging Continuously Differentiable Activation Functions for Learning in Quantized Noisy Environments Vivswan Shah Nathan Youngblood 81 2 0 04 Feb 2024
Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation D. Powers 175 5,293 0 11 Oct 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 99 73 0 07 Aug 2020
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 160 2,159 0 21 Aug 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 131 1,864 0 20 May 2017
Deep Text Classification Can be Fooled Bin Liang Hongcheng Li Miaoqiang Su Pan Bian Xirong Li Wenchang Shi AAML 75 425 0 26 Apr 2017
Adversarial and Clean Data Are Not Twins Zhitao Gong Wenlu Wang Wei-Shinn Ku AAML 59 157 0 17 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
Detecting Adversarial Samples from Artifacts Reuben Feinman Ryan R. Curtin S. Shintre Andrew B. Gardner AAML 93 894 0 01 Mar 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
Adversarial Examples Detection in Deep Networks with Convolutional Filter Statistics Xin Li Fuxin Li GAN AAML 113 365 0 22 Dec 2016
Learning Adversary-Resistant Deep Neural Networks Qinglong Wang Wenbo Guo Kaixuan Zhang Alexander Ororbia Masashi Sugiyama Xue Liu C. Lee Giles AAML 66 43 0 05 Dec 2016
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 472 3,148 0 04 Nov 2016
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 272 4,159 0 18 Oct 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 59 175 0 05 Oct 2016
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library Nicolas Papernot Fartash Faghri Nicholas Carlini Ian Goodfellow Reuben Feinman ... David Berthelot P. Hendricks Jonas Rauber Rujun Long Patrick McDaniel AAML 65 514 0 03 Oct 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 81 236 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 67 418 0 14 Jun 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 75 3,682 0 08 Feb 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 115 3,967 0 24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 154 4,905 0 14 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
Character-level Convolutional Networks for Text Classification Xiang Zhang Jiaqi Zhao Yann LeCun 268 6,130 0 04 Sep 2015
Deep Learning and Music Adversaries Corey Kereliuk Bob L. T. Sturm J. Larsen AAML 73 137 0 16 Jul 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,107 0 20 Dec 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 485 43,694 0 17 Sep 2014
Caffe: Convolutional Architecture for Fast Feature Embedding Yangqing Jia Evan Shelhamer Jeff Donahue Sergey Karayev Jonathan Long Ross B. Girshick S. Guadarrama Trevor Darrell VLM BDL 3DV 280 14,713 0 20 Jun 2014
Deep Learning Face Representation by Joint Identification-Verification Yi Sun Xiaogang Wang Xiaoou Tang CVBM 227 2,246 0 18 Jun 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 282 14,961 1 21 Dec 2013
Building high-level features using large scale unsupervised learning Quoc V. Le MarcÁurelio Ranzato R. Monga M. Devin Kai Chen G. Corrado J. Dean A. Ng SSL OffRL CVBM 122 2,272 0 29 Dec 2011