Mitigating Adversarial Effects Through Randomization

6 November 2017

Cihang Xie

Papers citing "Mitigating Adversarial Effects Through Randomization"

50 / 252 papers shown

Title
Multi-way Encoding for Robustness Donghyun Kim Sarah Adel Bargal Jianming Zhang Stan Sclaroff AAML 18 2 0 05 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
Enhancing Adversarial Defense by k-Winners-Take-All Chang Xiao Peilin Zhong Changxi Zheng AAML 24 97 0 25 May 2019
Thwarting finite difference adversarial attacks with output randomization Haidar Khan Daniel Park Azer Khan B. Yener SILM AAML 41 0 0 23 May 2019
ROSA: Robust Salient Object Detection against Adversarial Attacks Haofeng Li Guanbin Li Yizhou Yu AAML 16 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 77 1,231 0 29 Apr 2019
Adversarial Defense Through Network Profiling Based Path Extraction Yuxian Qiu Jingwen Leng Cong Guo Quan Chen Chong Li Minyi Guo Yuhao Zhu AAML 24 51 0 17 Apr 2019
Evaluating Robustness of Deep Image Super-Resolution against Adversarial Attacks Jun-Ho Choi Huan Zhang Jun-Hyuk Kim Cho-Jui Hsieh Jong-Seok Lee AAML SupR 24 70 0 12 Apr 2019
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks Yinpeng Dong Tianyu Pang Hang Su Jun Zhu SILM AAML 49 830 0 05 Apr 2019
Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks Aamir Mustafa Salman Khan Munawar Hayat Roland Göcke Jianbing Shen Ling Shao AAML 17 151 0 01 Apr 2019
Defending against adversarial attacks by randomized diversification O. Taran Shideh Rezaeifar T. Holotyak Slava Voloshynovskiy AAML 29 38 0 01 Apr 2019
On the Vulnerability of CNN Classifiers in EEG-Based BCIs Xiao Zhang Dongrui Wu AAML 24 82 0 31 Mar 2019
Defending against Whitebox Adversarial Attacks via Randomized Discretization Yuchen Zhang Percy Liang AAML 32 75 0 25 Mar 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
On Certifying Non-uniform Bound against Adversarial Attacks Chen Liu Ryota Tomioka V. Cevher AAML 50 19 0 15 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
Adversarial Attack and Defense on Point Sets Jiancheng Yang Qiang Zhang Rongyao Fang Bingbing Ni Jinxian Liu Qi Tian 3DPC 24 122 0 28 Feb 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
Adversarial Examples Are a Natural Consequence of Test Error in Noise Nic Ford Justin Gilmer Nicholas Carlini E. D. Cubuk AAML 36 318 0 29 Jan 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 22 144 0 15 Jan 2019
Image Super-Resolution as a Defense Against Adversarial Attacks Aamir Mustafa Salman H. Khan Munawar Hayat Jianbing Shen Ling Shao AAML SupR 27 168 0 07 Jan 2019
Adversarial Examples Versus Cloud-based Detectors: A Black-box Empirical Study Xurong Li S. Ji Men Han Juntao Ji Zhenyu Ren Yushan Liu Chunming Wu AAML 26 31 0 04 Jan 2019
On the Security of Randomized Defenses Against Adversarial Samples K. Sharad G. Marson H. Truong Ghassan O. Karame AAML 35 1 0 11 Dec 2018
Data Fine-tuning S. Chhabra P. Majumdar Mayank Vatsa Richa Singh AAML 20 13 0 10 Dec 2018
Learning Transferable Adversarial Examples via Ghost Networks Yingwei Li S. Bai Yuyin Zhou Cihang Xie Zhishuai Zhang Alan Yuille AAML 42 136 0 09 Dec 2018
Random Spiking and Systematic Evaluation of Defenses Against Adversarial Examples Huangyi Ge Sze Yiu Chau Bruno Ribeiro Ninghui Li AAML 27 1 0 05 Dec 2018
Universal Perturbation Attack Against Image Retrieval Jie Li Rongrong Ji Hong Liu Xiaopeng Hong Yue Gao Q. Tian AAML 29 98 0 03 Dec 2018
ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples Xiaojun Jia Xingxing Wei Xiaochun Cao H. Foroosh AAML 69 264 0 30 Nov 2018
MixTrain: Scalable Training of Verifiably Robust Neural Networks Yue Zhang Yizheng Chen Ahmed Abdou Mohsen Guizani AAML 27 23 0 06 Nov 2018
QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks Faiq Khalid Hassan Ali Hammad Tariq Muhammad Abdullah Hanif Semeen Rehman Rehan Ahmed Mohamed Bennai AAML MQ 35 37 0 04 Nov 2018
Sparse DNNs with Improved Adversarial Robustness Yiwen Guo Chao Zhang Changshui Zhang Yurong Chen AAML 25 151 0 23 Oct 2018
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation Chaowei Xiao Ruizhi Deng Bo Li Feng Yu M. Liu D. Song AAML 19 99 0 11 Oct 2018
CAAD 2018: Generating Transferable Adversarial Examples Yash Sharma Tien-Dung Le M. Alzantot AAML SILM 31 7 0 29 Sep 2018
Query-Efficient Black-Box Attack by Active Learning Pengcheng Li Jinfeng Yi Lijun Zhang AAML MLAU 21 54 0 13 Sep 2018
Are adversarial examples inevitable? Ali Shafahi Wenjie Huang Christoph Studer S. Feizi Tom Goldstein SILM 24 281 0 06 Sep 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
With Friends Like These, Who Needs Adversaries? Saumya Jetley Nicholas A. Lord Philip Torr AAML 21 70 0 11 Jul 2018
Efficient ConvNets for Analog Arrays Malte J. Rasch Tayfun Gokmen Mattia Rigotti W. Haensch 31 11 0 03 Jul 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
Deep Nets: What have they ever done for Vision? Alan Yuille Chenxi Liu 28 102 0 10 May 2018
An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks Pu Zhao Sijia Liu Yanzhi Wang Xinyu Lin AAML 28 37 0 09 Apr 2018
Adversarial Defense based on Structure-to-Signal Autoencoders Joachim Folz Sebastián M. Palacio Jörn Hees Damian Borth Andreas Dengel AAML 26 32 0 21 Mar 2018
Deep Defense: Training DNNs with Improved Adversarial Robustness Ziang Yan Yiwen Guo Changshui Zhang AAML 38 109 0 23 Feb 2018
Generative Adversarial Perturbations Omid Poursaeed Isay Katsman Bicheng Gao Serge J. Belongie AAML GAN WIGM 31 351 0 06 Dec 2017
Towards Robust Neural Networks via Random Self-ensemble Xuanqing Liu Minhao Cheng Huan Zhang Cho-Jui Hsieh FedML AAML 58 419 0 02 Dec 2017