Ensemble Adversarial Training: Attacks and Defenses

19 May 2017

Dan Boneh

Papers citing "Ensemble Adversarial Training: Attacks and Defenses"

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Title
Towards Repairing Neural Networks Correctly Guoliang Dong Jun Sun Jingyi Wang Xinyu Wang Ting Dai 22 23 0 03 Dec 2020
FAT: Federated Adversarial Training Giulio Zizzo Ambrish Rawat M. Sinn Beat Buesser FedML 33 43 0 03 Dec 2020
FenceBox: A Platform for Defeating Adversarial Examples with Data Augmentation Techniques Han Qiu Yi Zeng Tianwei Zhang Yong-jia Jiang Meikang Qiu AAML 17 15 0 03 Dec 2020
Visually Imperceptible Adversarial Patch Attacks on Digital Images Yaguan Qian Jiamin Wang Bin Wang Xiang Ling Zhaoquan Gu Chunming Wu Wassim Swaileh AAML 44 2 0 02 Dec 2020
Boosting Adversarial Attacks on Neural Networks with Better Optimizer Heng Yin Hengwei Zhang Jin-dong Wang Ruiyu Dou AAML 40 8 0 01 Dec 2020
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Gaurang Sriramanan Sravanti Addepalli Arya Baburaj R. Venkatesh Babu AAML 28 92 0 30 Nov 2020
Deterministic Certification to Adversarial Attacks via Bernstein Polynomial Approximation Ching-Chia Kao Jhe-Bang Ko Chun-Shien Lu AAML 32 1 0 28 Nov 2020
Incorporating Hidden Layer representation into Adversarial Attacks and Defences Haojing Shen Sihong Chen Ran Wang Xizhao Wang AAML 16 0 0 28 Nov 2020
Voting based ensemble improves robustness of defensive models Devvrit Minhao Cheng Cho-Jui Hsieh Inderjit Dhillon OOD FedML AAML 44 12 0 28 Nov 2020
A Study on the Uncertainty of Convolutional Layers in Deep Neural Networks Hao Shen Sihong Chen Ran Wang 30 5 0 27 Nov 2020
Exposing the Robustness and Vulnerability of Hybrid 8T-6T SRAM Memory Architectures to Adversarial Attacks in Deep Neural Networks Abhishek Moitra Priyadarshini Panda AAML 32 2 0 26 Nov 2020
Omni: Automated Ensemble with Unexpected Models against Adversarial Evasion Attack Rui Shu Tianpei Xia Laurie A. Williams Tim Menzies AAML 32 15 0 23 Nov 2020
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu Liu Liwei Wang Jiaya Jia OOD AAML 32 126 0 23 Nov 2020
Contextual Fusion For Adversarial Robustness Aiswarya Akumalla S. Haney M. Bazhenov AAML 27 1 0 18 Nov 2020
On the Transferability of Adversarial Attacksagainst Neural Text Classifier Liping Yuan Xiaoqing Zheng Yi Zhou Cho-Jui Hsieh Kai-Wei Chang SILM AAML 19 26 0 17 Nov 2020
Extreme Value Preserving Networks Mingjie Sun Jianguo Li Changshui Zhang AAML MDE 8 0 0 17 Nov 2020
Towards Understanding the Regularization of Adversarial Robustness on Neural Networks Yuxin Wen Shuai Li Kui Jia AAML 26 24 0 15 Nov 2020
Fooling the primate brain with minimal, targeted image manipulation Li-xin Yuan Will Xiao Giorgia Dellaferrera Gabriel Kreiman Francis E. H. Tay Jiashi Feng Margaret Livingstone AAML 36 1 0 11 Nov 2020
Risk Assessment for Machine Learning Models Paul Schwerdtner Florens Greßner Nikhil Kapoor F. Assion René Sass W. Günther Fabian Hüger Peter Schlicht 19 6 0 09 Nov 2020
Adversarial Counterfactual Learning and Evaluation for Recommender System Da Xu Chuanwei Ruan Evren Körpeoglu Sushant Kumar Kannan Achan OffRL CML 22 33 0 08 Nov 2020
Amadeus: Scalable, Privacy-Preserving Live Video Analytics Sandeep M. D'Souza P. Bahl Lixiang Ao Landon P. Cox 26 8 0 06 Nov 2020
Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks Leo Schwinn An Nguyen René Raab Dario Zanca Bjoern M. Eskofier Daniel Tenbrinck Martin Burger AAML 27 8 0 05 Nov 2020
Defense-friendly Images in Adversarial Attacks: Dataset and Metrics for Perturbation Difficulty Camilo Pestana Wei Liu D. Glance Ajmal Mian AAML 21 5 0 05 Nov 2020
A Tunable Robust Pruning Framework Through Dynamic Network Rewiring of DNNs Souvik Kundu M. Nazemi Peter A. Beerel Massoud Pedram AAML 18 67 0 03 Nov 2020
Trustworthy AI Richa Singh Mayank Vatsa Nalini Ratha 28 4 0 02 Nov 2020
The Vulnerability of the Neural Networks Against Adversarial Examples in Deep Learning Algorithms Rui Zhao AAML 34 1 0 02 Nov 2020
LG-GAN: Label Guided Adversarial Network for Flexible Targeted Attack of Point Cloud-based Deep Networks Hang Zhou Dongdong Chen Jing Liao Weiming Zhang Kejiang Chen Xiaoyi Dong Kunlin Liu G. Hua Nenghai Yu 3DPC 21 99 0 01 Nov 2020
MAD-VAE: Manifold Awareness Defense Variational Autoencoder Frederick Morlock Dingsu Wang AAML DRL 24 2 0 31 Oct 2020
Evaluation of Inference Attack Models for Deep Learning on Medical Data Maoqiang Wu Xinyue Zhang Jiahao Ding H. Nguyen Rong Yu Miao Pan Stephen T. C. Wong MIACV 20 18 0 31 Oct 2020
Capture the Bot: Using Adversarial Examples to Improve CAPTCHA Robustness to Bot Attacks Dorjan Hitaj Briland Hitaj S. Jajodia L. Mancini AAML 14 17 0 30 Oct 2020
Perception Improvement for Free: Exploring Imperceptible Black-box Adversarial Attacks on Image Classification Yongwei Wang Mingquan Feng Rabab Ward Z. J. Wang Lanjun Wang AAML 27 3 0 30 Oct 2020
GreedyFool: Distortion-Aware Sparse Adversarial Attack Xiaoyi Dong Dongdong Chen Jianmin Bao Chuan Qin Lu Yuan Weiming Zhang Nenghai Yu Dong Chen AAML 18 63 0 26 Oct 2020
Attack Agnostic Adversarial Defense via Visual Imperceptible Bound S. Chhabra Akshay Agarwal Richa Singh Mayank Vatsa AAML 39 3 0 25 Oct 2020
ATRO: Adversarial Training with a Rejection Option Masahiro Kato Zhenghang Cui Yoshihiro Fukuhara AAML 31 11 0 24 Oct 2020
Concealed Data Poisoning Attacks on NLP Models Eric Wallace Tony Zhao Shi Feng Sameer Singh SILM 33 18 0 23 Oct 2020
Deep Neural Mobile Networking Chaoyun Zhang 32 1 0 23 Oct 2020
Towards Robust Neural Networks via Orthogonal Diversity Kun Fang Qinghua Tao Yingwen Wu Tao Li Jia Cai Feipeng Cai Xiaolin Huang Jie Yang AAML 41 8 0 23 Oct 2020
Contrastive Learning with Adversarial Examples Chih-Hui Ho Nuno Vasconcelos SSL 27 140 0 22 Oct 2020
Defense-guided Transferable Adversarial Attacks Zifei Zhang Kai Qiao Jian Chen Ningning Liang AAML 19 0 0 22 Oct 2020
Learning Black-Box Attackers with Transferable Priors and Query Feedback Jiancheng Yang Yangzhou Jiang Xiaoyang Huang Bingbing Ni Chenglong Zhao AAML 18 81 0 21 Oct 2020
Boosting Gradient for White-Box Adversarial Attacks Hongying Liu Zhenyu Zhou Fanhua Shang Xiaoyu Qi Yuanyuan Liu L. Jiao AAML 32 7 0 21 Oct 2020
Progressive Defense Against Adversarial Attacks for Deep Learning as a Service in Internet of Things Ling Wang Cheng Zhang Zejian Luo Chenguang Liu Jie Liu Xi Zheng A. Vasilakos AAML 25 3 0 15 Oct 2020
Security and Privacy Considerations for Machine Learning Models Deployed in the Government and Public Sector (white paper) Nader Sehatbakhsh E. Daw O. Savas Amin Hassanzadeh I. Mcculloh SILM 19 1 0 12 Oct 2020
Distributionally Robust Local Non-parametric Conditional Estimation Viet Anh Nguyen Fan Zhang Jose H. Blanchet Erick Delage Yinyu Ye OOD 20 26 0 12 Oct 2020
Understanding Local Robustness of Deep Neural Networks under Natural Variations Ziyuan Zhong Yuchi Tian Baishakhi Ray AAML 19 1 0 09 Oct 2020
A Unified Approach to Interpreting and Boosting Adversarial Transferability Xin Eric Wang Jie Ren Shuyu Lin Xiangming Zhu Yisen Wang Quanshi Zhang AAML 34 94 0 08 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 22 325 0 07 Oct 2020
Don't Trigger Me! A Triggerless Backdoor Attack Against Deep Neural Networks A. Salem Michael Backes Yang Zhang 16 35 0 07 Oct 2020
Understanding Classifier Mistakes with Generative Models Laetitia Shao Yang Song Stefano Ermon 6 4 0 05 Oct 2020
Understanding Catastrophic Overfitting in Single-step Adversarial Training Hoki Kim Woojin Lee Jaewook Lee AAML 16 108 0 05 Oct 2020