Ensemble Adversarial Training: Attacks and Defenses

19 May 2017

Dan Boneh

Papers citing "Ensemble Adversarial Training: Attacks and Defenses"

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Title
Conservative Objective Models for Effective Offline Model-Based Optimization Brandon Trabucco Aviral Kumar Xinyang Geng Sergey Levine OffRL 36 86 0 14 Jul 2021
Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks Xiao Yang Yinpeng Dong Tianyu Pang Hang Su Jun Zhu AAML 38 38 0 05 Jul 2021
Adversarial Visual Robustness by Causal Intervention Kaihua Tang Ming Tao Hanwang Zhang CML AAML 27 21 0 17 Jun 2021
Code Integrity Attestation for PLCs using Black Box Neural Network Predictions Yuqi Chen Christopher M. Poskitt Jun Sun AAML 20 9 0 15 Jun 2021
Sparta: Spatially Attentive and Adversarially Robust Activation Qing-Wu Guo Felix Juefei Xu Changqing Zhou Wei Feng Yang Liu Song Wang AAML 25 4 0 18 May 2021
Salient Feature Extractor for Adversarial Defense on Deep Neural Networks Jinyin Chen Ruoxi Chen Haibin Zheng Zhaoyan Ming Wenrong Jiang Chen Cui AAML 25 10 0 14 May 2021
Multi-Robot Coordination and Planning in Uncertain and Adversarial Environments Lifeng Zhou Pratap Tokekar 34 43 0 02 May 2021
Random Noise Defense Against Query-Based Black-Box Attacks Zeyu Qin Yanbo Fan H. Zha Baoyuan Wu AAML 19 59 0 23 Apr 2021
Robust Sensor Fusion Algorithms Against Voice Command Attacks in Autonomous Vehicles Jiwei Guan Xi Zheng Chen Wang Yipeng Zhou A. Jolfaei AAML 17 5 0 20 Apr 2021
Staircase Sign Method for Boosting Adversarial Attacks Qilong Zhang Xiaosu Zhu Jingkuan Song Lianli Gao Heng Tao Shen AAML 35 13 0 20 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 29 65 0 09 Apr 2021
Class-Aware Robust Adversarial Training for Object Detection Pin-Chun Chen Bo-Han Kung Jun-Cheng Chen AAML ObjD 18 48 0 30 Mar 2021
Privacy and Trust Redefined in Federated Machine Learning Pavlos Papadopoulos Will Abramson A. Hall Nikolaos Pitropakis William J. Buchanan 33 42 0 29 Mar 2021
Enhancing the Transferability of Adversarial Attacks through Variance Tuning Xiaosen Wang Kun He AAML 19 376 0 29 Mar 2021
SoK: A Modularized Approach to Study the Security of Automatic Speech Recognition Systems Yuxuan Chen Jiangshan Zhang Xuejing Yuan Shengzhi Zhang Kai Chen Xiaofeng Wang Shanqing Guo AAML 37 15 0 19 Mar 2021
Generating Unrestricted Adversarial Examples via Three Parameters Hanieh Naderi Leili Goli S. Kasaei 35 8 0 13 Mar 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 30 268 0 02 Mar 2021
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness Jacob D. Abernethy Pranjal Awasthi Satyen Kale AAML 24 6 0 01 Mar 2021
Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids Jiangnan Li Yingyuan Yang Jinyuan Stella Sun K. Tomsovic Hairong Qi AAML 31 14 0 17 Feb 2021
Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS Felix O. Olowononi D. Rawat Chunmei Liu 34 132 0 14 Feb 2021
Quantifying and Mitigating Privacy Risks of Contrastive Learning Xinlei He Yang Zhang 11 51 0 08 Feb 2021
Adversarial Attacks and Defenses in Physiological Computing: A Systematic Review Dongrui Wu Jiaxin Xu Weili Fang Yi Zhang Liuqing Yang Xiaodong Xu Hanbin Luo Xiang Yu AAML 21 25 0 04 Feb 2021
Robust Adversarial Attacks Against DNN-Based Wireless Communication Systems Alireza Bahramali Milad Nasr Amir Houmansadr Dennis Goeckel Don Towsley AAML 34 53 0 01 Feb 2021
Increasing the Confidence of Deep Neural Networks by Coverage Analysis Giulio Rossolini Alessandro Biondi Giorgio Buttazzo AAML 26 13 0 28 Jan 2021
Robust Android Malware Detection System against Adversarial Attacks using Q-Learning Hemant Rathore S. K. Sahay Piyush Nikam Mohit Sewak AAML 16 61 0 27 Jan 2021
Generalizing Adversarial Examples by AdaBelief Optimizer Yixiang Wang Jiqiang Liu Xiaolin Chang AAML 14 1 0 25 Jan 2021
Practical Blind Membership Inference Attack via Differential Comparisons Bo Hui Yuchen Yang Haolin Yuan Philippe Burlina Neil Zhenqiang Gong Yinzhi Cao MIACV 30 119 0 05 Jan 2021
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead Muhammad Shafique Mahum Naseer T. Theocharides C. Kyrkou O. Mutlu Lois Orosa Jungwook Choi OOD 75 100 0 04 Jan 2021
Local Competition and Stochasticity for Adversarial Robustness in Deep Learning Konstantinos P. Panousis S. Chatzis Antonios Alexos Sergios Theodoridis BDL AAML OOD 56 19 0 04 Jan 2021
On Success and Simplicity: A Second Look at Transferable Targeted Attacks Zhengyu Zhao Zhuoran Liu Martha Larson AAML 24 121 0 21 Dec 2020
A Closer Look at the Robustness of Vision-and-Language Pre-trained Models Linjie Li Zhe Gan Jingjing Liu VLM 33 42 0 15 Dec 2020
Hypothesis Disparity Regularized Mutual Information Maximization Qicheng Lao Xiang Jiang Mohammad Havaei 30 24 0 15 Dec 2020
Achieving Adversarial Robustness Requires An Active Teacher Chao Ma Lexing Ying 21 1 0 14 Dec 2020
Locally optimal detection of stochastic targeted universal adversarial perturbations Amish Goel P. Moulin AAML 12 2 0 08 Dec 2020
FAT: Federated Adversarial Training Giulio Zizzo Ambrish Rawat M. Sinn Beat Buesser FedML 25 43 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 22 2 0 02 Dec 2020
Boosting Adversarial Attacks on Neural Networks with Better Optimizer Heng Yin Hengwei Zhang Jin-dong Wang Ruiyu Dou AAML 14 8 0 01 Dec 2020
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Gaurang Sriramanan Sravanti Addepalli Arya Baburaj R. Venkatesh Babu AAML 8 92 0 30 Nov 2020
A Study on the Uncertainty of Convolutional Layers in Deep Neural Networks Hao Shen Sihong Chen Ran Wang 27 5 0 27 Nov 2020
Omni: Automated Ensemble with Unexpected Models against Adversarial Evasion Attack Rui Shu Tianpei Xia Laurie A. Williams Tim Menzies AAML 24 15 0 23 Nov 2020
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu-Lin Liu Liwei Wang Jiaya Jia OOD AAML 19 124 0 23 Nov 2020
Contextual Fusion For Adversarial Robustness Aiswarya Akumalla S. Haney M. Bazhenov AAML 22 1 0 18 Nov 2020
The Vulnerability of the Neural Networks Against Adversarial Examples in Deep Learning Algorithms Rui Zhao AAML 21 1 0 02 Nov 2020
Concealed Data Poisoning Attacks on NLP Models Eric Wallace Tony Zhao Shi Feng Sameer Singh SILM 11 18 0 23 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
A Unified Approach to Interpreting and Boosting Adversarial Transferability Xin Wang Jie Ren Shuyu Lin Xiangming Zhu Yisen Wang Quanshi Zhang AAML 26 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 17 323 0 07 Oct 2020
Understanding Catastrophic Overfitting in Single-step Adversarial Training Hoki Kim Woojin Lee Jaewook Lee AAML 11 107 0 05 Oct 2020
Generating Adversarial yet Inconspicuous Patches with a Single Image Jinqi Luo Tao Bai Jun Zhao AAML 27 6 0 21 Sep 2020
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 19 11 0 21 Sep 2020