Two Souls in an Adversarial Image: Towards Universal Adversarial Example Detection using Multi-view Inconsistency

25 September 2021

Papers citing "Two Souls in an Adversarial Image: Towards Universal Adversarial Example Detection using Multi-view Inconsistency"

48 / 48 papers shown

Title
Anytime Sampling for Autoregressive Models via Ordered Autoencoding Yilun Xu Yang Song Sahaj Garg Linyuan Gong Rui Shu Aditya Grover Stefano Ermon DiffM 55 11 0 23 Feb 2021
Beating Attackers At Their Own Games: Adversarial Example Detection Using Adversarial Gradient Directions Yuhang Wu Sunpreet S. Arora Yanhong Wu Hao Yang AAML 26 9 0 31 Dec 2020
An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks Ruixiang Tang Mengnan Du Ninghao Liu Fan Yang Xia Hu AAML 41 185 0 15 Jun 2020
Adversarial Detection and Correction by Matching Prediction Distributions G. Vacanti A. V. Looveren AAML 90 16 0 21 Feb 2020
On Adaptive Attacks to Adversarial Example Defenses Florian Tramèr Nicholas Carlini Wieland Brendel Aleksander Madry AAML 197 827 0 19 Feb 2020
A Survey of Deep Learning Techniques for Autonomous Driving Sorin Grigorescu Bogdan Trasnea Tiberiu T. Cocias G. Macesanu 3DPC 62 1,392 0 17 Oct 2019
Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors Gilad Cohen Guillermo Sapiro Raja Giryes TDI 32 125 0 15 Sep 2019
Demon in the Variant: Statistical Analysis of DNNs for Robust Backdoor Contamination Detection Di Tang Xiaofeng Wang Haixu Tang Kehuan Zhang AAML 43 198 0 02 Aug 2019
Are Odds Really Odd? Bypassing Statistical Detection of Adversarial Examples Hossein Hosseini Sreeram Kannan Radha Poovendran AAML 34 18 0 28 Jul 2019
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions Yao Qin Nicholas Frosst S. Sabour Colin Raffel G. Cottrell Geoffrey E. Hinton GAN AAML 34 72 0 05 Jul 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 80 1,825 0 06 May 2019
A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning Shahbaz Rezaei Xin Liu SILM AAML 108 46 0 08 Apr 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth Yannic Kilcher Thomas Hofmann AAML 44 175 0 13 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 106 2,018 0 08 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 98 2,525 0 24 Jan 2019
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 120 2,024 0 10 Jul 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 88 1,772 0 30 May 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei Maya Kabkab Rama Chellappa AAML GAN 67 1,172 0 17 May 2018
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks Ali Shafahi Wenjie Huang Mahyar Najibi Octavian Suciu Christoph Studer Tudor Dumitras Tom Goldstein AAML 78 1,080 0 03 Apr 2018
Adversarial Examples that Fool both Computer Vision and Time-Limited Humans Gamaleldin F. Elsayed Shreya Shankar Brian Cheung Nicolas Papernot Alexey Kurakin Ian Goodfellow Jascha Narain Sohl-Dickstein AAML 64 261 0 22 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 164 3,171 0 01 Feb 2018
Generating Adversarial Examples with Adversarial Networks Chaowei Xiao Yue Liu Jun-Yan Zhu Warren He M. Liu D. Song GAN AAML 107 893 0 08 Jan 2018
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples Yang Song Taesup Kim Sebastian Nowozin Stefano Ermon Nate Kushman AAML 97 787 0 30 Oct 2017
Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification Xiaoyu Cao Neil Zhenqiang Gong AAML 47 209 0 17 Sep 2017
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 106 2,142 0 21 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 236 11,962 0 19 Jun 2017
Certified Defenses for Data Poisoning Attacks Jacob Steinhardt Pang Wei Koh Percy Liang AAML 75 751 0 09 Jun 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 103 1,851 0 20 May 2017
Fast Generation for Convolutional Autoregressive Models Prajit Ramachandran T. Paine Pooya Khorrami Mohammad Babaeizadeh Shiyu Chang Yang Zhang Mark Hasegawa-Johnson R. Campbell Thomas S. Huang BDL 49 67 0 20 Apr 2017
Adversarial and Clean Data Are Not Twins Zhitao Gong Wenlu Wang Wei-Shinn Ku AAML 46 156 0 17 Apr 2017
Detecting Adversarial Samples from Artifacts Reuben Feinman Ryan R. Curtin S. Shintre Andrew B. Gardner AAML 77 892 0 01 Mar 2017
On the (Statistical) Detection of Adversarial Examples Kathrin Grosse Praveen Manoharan Nicolas Papernot Michael Backes Patrick McDaniel AAML 65 710 0 21 Feb 2017
On Detecting Adversarial Perturbations J. H. Metzen Tim Genewein Volker Fischer Bastian Bischoff AAML 49 947 0 14 Feb 2017
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications Tim Salimans A. Karpathy Xi Chen Diederik P. Kingma 62 933 0 19 Jan 2017
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 49 512 0 03 Oct 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 174 8,513 0 16 Aug 2016
Early Methods for Detecting Adversarial Images Dan Hendrycks Kevin Gimpel AAML 61 236 0 01 Aug 2016
Conditional Image Generation with PixelCNN Decoders Aaron van den Oord Nal Kalchbrenner Oriol Vinyals L. Espeholt Alex Graves Koray Kavukcuoglu VLM 138 2,495 0 16 Jun 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 272 7,951 0 23 May 2016
Neural Autoregressive Distribution Estimation Benigno Uria Marc-Alexandre Côté Karol Gregor Iain Murray Hugo Larochelle 70 314 0 07 May 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 405 2,563 0 25 Jan 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 69 3,947 0 24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 100 4,878 0 14 Nov 2015
DeepID3: Face Recognition with Very Deep Neural Networks Yi Sun Ding Liang Xiaogang Wang Xiaoou Tang CVBM 73 940 0 03 Feb 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 184 18,922 0 20 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 136 3,261 0 05 Dec 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.2K 39,383 0 01 Sep 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 192 14,831 1 21 Dec 2013