PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples

30 October 2017

Papers citing "PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples"

50 / 157 papers shown

Title
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 67 63 0 02 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 47 785 0 26 Feb 2020
Adversarial Detection and Correction by Matching Prediction Distributions G. Vacanti A. V. Looveren AAML 14 15 0 21 Feb 2020
Deflecting Adversarial Attacks Yao Qin Nicholas Frosst Colin Raffel G. Cottrell Geoffrey E. Hinton AAML 30 15 0 18 Feb 2020
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence S. Raschka Joshua Patterson Corey J. Nolet AI4CE 24 484 0 12 Feb 2020
Minimax Defense against Gradient-based Adversarial Attacks Blerta Lindqvist R. Izmailov AAML 19 0 0 04 Feb 2020
Towards Sharper First-Order Adversary with Quantized Gradients Zhuanghua Liu Ivor W. Tsang AAML 19 0 0 01 Feb 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 99 1,158 0 12 Jan 2020
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 28 36 0 26 Dec 2019
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Jackson Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 43 528 0 06 Dec 2019
One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples Chang Xiao Changxi Zheng AAML 25 19 0 25 Nov 2019
Invert and Defend: Model-based Approximate Inversion of Generative Adversarial Networks for Secure Inference Wei-An Lin Yogesh Balaji Pouya Samangouei Rama Chellappa 33 6 0 23 Nov 2019
Defective Convolutional Networks Tiange Luo Tianle Cai Mengxiao Zhang Siyu Chen Di He Liwei Wang AAML 30 3 0 19 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 18 104 0 13 Nov 2019
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 37 68 0 06 Nov 2019
Adversarial Example Detection by Classification for Deep Speech Recognition Saeid Samizade Zheng-Hua Tan Chao Shen X. Guan AAML 18 35 0 22 Oct 2019
A New Defense Against Adversarial Images: Turning a Weakness into a Strength Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 58 101 0 16 Oct 2019
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts Yu Sun Xiaolong Wang Zhuang Liu John Miller Alexei A. Efros Moritz Hardt TTA OOD 27 92 0 29 Sep 2019
Defending Against Adversarial Iris Examples Using Wavelet Decomposition Sobhan Soleymani Ali Dabouei J. Dawson Nasser M. Nasrabadi AAML 27 9 0 08 Aug 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 23 230 0 24 Jul 2019
Towards Adversarially Robust Object Detection Haichao Zhang Jianyu Wang AAML ObjD 23 130 0 24 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 19 71 0 05 Jul 2019
Evolving Robust Neural Architectures to Defend from Adversarial Attacks Shashank Kotyan Danilo Vasconcellos Vargas OOD AAML 24 36 0 27 Jun 2019
Defending Against Adversarial Attacks Using Random Forests Yifan Ding Liqiang Wang Huan Zhang Jinfeng Yi Deliang Fan Boqing Gong AAML 13 14 0 16 Jun 2019
ML-LOO: Detecting Adversarial Examples with Feature Attribution Puyudi Yang Jianbo Chen Cho-Jui Hsieh Jane-ling Wang Michael I. Jordan AAML 22 101 0 08 Jun 2019
Enhancing Gradient-based Attacks with Symbolic Intervals Shiqi Wang Yizheng Chen Ahmed Abdou Suman Jana AAML 28 15 0 05 Jun 2019
Enhancing Transformation-based Defenses using a Distribution Classifier C. Kou H. Lee E. Chang Teck Khim Ng 34 3 0 01 Jun 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward A. Qayyum Muhammad Usama Junaid Qadir Ala I. Al-Fuqaha AAML 21 187 0 29 May 2019
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation Yuzhe Yang Guo Zhang Dina Katabi Zhi Xu AAML 10 168 0 28 May 2019
Purifying Adversarial Perturbation with Adversarially Trained Auto-encoders Hebi Li Qi Xiao Shixin Tian Jin Tian AAML 24 4 0 26 May 2019
Enhancing Adversarial Defense by k-Winners-Take-All Chang Xiao Peilin Zhong Changxi Zheng AAML 24 97 0 25 May 2019
ROSA: Robust Salient Object Detection against Adversarial Attacks Haofeng Li Guanbin Li Yizhou Yu AAML 10 28 0 09 May 2019
Adversarial Training for Free! Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 68 1,227 0 29 Apr 2019
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks Yinpeng Dong Tianyu Pang Hang Su Jun Zhu SILM AAML 49 828 0 05 Apr 2019
Variational Inference with Latent Space Quantization for Adversarial Resilience Vinay Kyatham P. PrathoshA. Tarun Kumar Yadav Deepak Mishra Dheeraj Mundhra AAML 19 3 0 24 Mar 2019
Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search Abhimanyu Dubey L. V. D. van der Maaten Zeki Yalniz Yixuan Li D. Mahajan AAML 33 62 0 05 Mar 2019
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations Saeid Asgari Taghanaki Kumar Abhishek Shekoofeh Azizi Ghassan Hamarneh AAML 31 40 0 03 Mar 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth Yannic Kilcher Thomas Hofmann AAML 27 175 0 13 Feb 2019
Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples Derui Wang Chaoran Li S. Wen Qing-Long Han Surya Nepal Xiangyu Zhang Yang Xiang AAML 30 40 0 06 Feb 2019
The Limitations of Adversarial Training and the Blind-Spot Attack Huan Zhang Hongge Chen Zhao Song Duane S. Boning Inderjit S. Dhillon Cho-Jui Hsieh AAML 19 144 0 15 Jan 2019
AutoGAN: Robust Classifier Against Adversarial Attacks Blerta Lindqvist Shridatt Sugrim R. Izmailov AAML 29 7 0 08 Dec 2018
MixTrain: Scalable Training of Verifiably Robust Neural Networks Yue Zhang Yizheng Chen Ahmed Abdou Mohsen Guizani AAML 21 23 0 06 Nov 2018
WAIC, but Why? Generative Ensembles for Robust Anomaly Detection Hyun-Jae Choi Eric Jang Alexander A. Alemi OODD 20 82 0 02 Oct 2018
DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing Xiaofei Xie Lei Ma Felix Juefei Xu Hongxu Chen Minhui Xue Bo-wen Li Yang Liu Jianjun Zhao Jianxiong Yin Simon See 43 40 0 04 Sep 2018
Distributionally Adversarial Attack T. Zheng Changyou Chen K. Ren OOD 18 121 0 16 Aug 2018
Motivating the Rules of the Game for Adversarial Example Research Justin Gilmer Ryan P. Adams Ian Goodfellow David G. Andersen George E. Dahl AAML 50 226 0 18 Jul 2018
Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders Partha Ghosh Arpan Losalka Michael J. Black AAML 21 77 0 31 May 2018
Defending Against Adversarial Attacks by Leveraging an Entire GAN G. Santhanam Paulina Grnarova AAML 16 40 0 27 May 2018
Towards the first adversarially robust neural network model on MNIST Lukas Schott Jonas Rauber Matthias Bethge Wieland Brendel AAML OOD 14 369 0 23 May 2018
VectorDefense: Vectorization as a Defense to Adversarial Examples V. Kabilan Brandon L. Morris Anh Totti Nguyen AAML 22 21 0 23 Apr 2018