Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models

17 May 2018

Papers citing "Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models"

50 / 252 papers shown

Title
ShapeAdv: Generating Shape-Aware Adversarial 3D Point Clouds Kibok Lee Zhuoyuan Chen Xinchen Yan R. Urtasun Ersin Yumer 3DPC 23 30 0 24 May 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 39 148 0 20 May 2020
Encryption Inspired Adversarial Defense for Visual Classification Maungmaung Aprilpyone Hitoshi Kiya 24 32 0 16 May 2020
GraCIAS: Grassmannian of Corrupted Images for Adversarial Security Ankita Shukla Pavan Turaga Saket Anand AAML 16 1 0 06 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 49 371 0 30 Apr 2020
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning Xinjian Luo Xiangqi Zhu FedML 78 25 0 27 Apr 2020
Ensemble Generative Cleaning with Feedback Loops for Defending Adversarial Attacks Jianhe Yuan Zhihai He AAML 32 22 0 23 Apr 2020
Single-step Adversarial training with Dropout Scheduling S. VivekB. R. Venkatesh Babu OOD AAML 18 71 0 18 Apr 2020
Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation Xingang Pan Xiaohang Zhan Bo Dai Dahua Lin Chen Change Loy Ping Luo DiffM 55 359 0 30 Mar 2020
Toward Adversarial Robustness via Semi-supervised Robust Training Yiming Li Baoyuan Wu Yan Feng Yanbo Fan Yong Jiang Zhifeng Li Shutao Xia AAML 87 13 0 16 Mar 2020
Diversity can be Transferred: Output Diversification for White- and Black-box Attacks Y. Tashiro Yang Song Stefano Ermon AAML 14 13 0 15 Mar 2020
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization Saehyung Lee Hyungyu Lee Sungroh Yoon AAML 163 113 0 05 Mar 2020
Differentially Private Deep Learning with Smooth Sensitivity Lichao Sun Yingbo Zhou Philip S. Yu Caiming Xiong FedML 26 9 0 01 Mar 2020
Real-Time Detectors for Digital and Physical Adversarial Inputs to Perception Systems Y. Kantaros Taylor J. Carpenter Kaustubh Sridhar Yahan Yang Insup Lee James Weimer AAML 17 12 0 23 Feb 2020
Adversarial Detection and Correction by Matching Prediction Distributions G. Vacanti A. V. Looveren AAML 14 16 0 21 Feb 2020
AI-GAN: Attack-Inspired Generation of Adversarial Examples Tao Bai Jun Zhao Jinlin Zhu Shoudong Han Jiefeng Chen Bo-wen Li Alex C. Kot GAN 39 48 0 06 Feb 2020
Minimax Defense against Gradient-based Adversarial Attacks Blerta Lindqvist R. Izmailov AAML 19 0 0 04 Feb 2020
Defending Adversarial Attacks via Semantic Feature Manipulation Shuo Wang Tianle Chen Surya Nepal Carsten Rudolph M. Grobler Shangyu Chen AAML 24 5 0 03 Feb 2020
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications Jie Gui Zhenan Sun Yonggang Wen Dacheng Tao Jieping Ye EGVM 33 821 0 20 Jan 2020
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 31 36 0 26 Dec 2019
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable Bytes Keane Lucas Mahmood Sharif Lujo Bauer Michael K. Reiter S. Shintre AAML 31 67 0 19 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
Fine-grained Synthesis of Unrestricted Adversarial Examples Omid Poursaeed Tianxing Jiang Yordanos Goshu Harry Yang Serge J. Belongie Ser-Nam Lim AAML 37 13 0 20 Nov 2019
Defective Convolutional Networks Tiange Luo Tianle Cai Mengxiao Zhang Siyu Chen Di He Liwei Wang AAML 35 3 0 19 Nov 2019
Adversarial Embedding: A robust and elusive Steganography and Watermarking technique Salah Ghamizi Maxime Cordy Mike Papadakis Yves Le Traon WIGM AAML 15 7 0 14 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 21 104 0 13 Nov 2019
Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training? Ali Shafahi Amin Ghiasi Furong Huang Tom Goldstein AAML 27 40 0 25 Oct 2019
Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets Yogesh Balaji Tom Goldstein Judy Hoffman AAML 134 103 0 17 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
Improving Password Guessing via Representation Learning Dario Pasquini Ankit Gangwal G. Ateniese M. Bernaschi Mauro Conti OOD 19 71 0 09 Oct 2019
SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations Ali Dabouei Sobhan Soleymani Fariborz Taherkhani J. Dawson Nasser M. Nasrabadi AAML 104 19 0 08 Oct 2019
Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions He Zhao Trung Le Paul Montague O. Vel Tamas Abraham Dinh Q. Phung AAML 28 8 0 03 Oct 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 24 18 0 27 Sep 2019
Metric Learning for Adversarial Robustness Chengzhi Mao Ziyuan Zhong Junfeng Yang Carl Vondrick Baishakhi Ray OOD 27 184 0 03 Sep 2019
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks Ka-Ho Chow Wenqi Wei Yanzhao Wu Ling Liu AAML 25 15 0 21 Aug 2019
DAPAS : Denoising Autoencoder to Prevent Adversarial attack in Semantic Segmentation Seungju Cho Tae Joon Jun Byungsoo Oh Daeyoung Kim 27 31 0 14 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 25 130 0 24 Jul 2019
Fast and Provable ADMM for Learning with Generative Priors Fabian Latorre Gómez Armin Eftekhari V. Cevher GAN 30 43 0 07 Jul 2019
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness Fanny Yang Zuowen Wang C. Heinze-Deml 28 42 0 26 Jun 2019
Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection Kang Liu Haoyu Yang Yuzhe Ma Benjamin Tan Bei Yu Evangeline F. Y. Young Ramesh Karri S. Garg AAML 20 10 0 25 Jun 2019
A unified view on differential privacy and robustness to adversarial examples Rafael Pinot Florian Yger Cédric Gouy-Pailler Jamal Atif AAML 21 17 0 19 Jun 2019
Towards Stable and Efficient Training of Verifiably Robust Neural Networks Huan Zhang Hongge Chen Chaowei Xiao Sven Gowal Robert Stanforth Bo-wen Li Duane S. Boning Cho-Jui Hsieh AAML 17 344 0 14 Jun 2019
Enhancing Transformation-based Defenses using a Distribution Classifier C. Kou H. Lee E. Chang Teck Khim Ng 37 3 0 01 Jun 2019
Robust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness Adnan Siraj Rakin Zhezhi He Li Yang Yanzhi Wang Liqiang Wang Deliang Fan AAML 40 21 0 30 May 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 27 187 0 29 May 2019
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation Yuzhe Yang Guo Zhang Dina Katabi Zhi Xu AAML 15 168 0 28 May 2019
Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss Pengcheng Li Jinfeng Yi Bowen Zhou Lijun Zhang AAML 37 36 0 28 May 2019
Purifying Adversarial Perturbation with Adversarially Trained Auto-encoders Hebi Li Qi Xiao Shixin Tian Jin Tian AAML 27 4 0 26 May 2019