Ensemble Adversarial Training: Attacks and Defenses

19 May 2017

Dan Boneh

Papers citing "Ensemble Adversarial Training: Attacks and Defenses"

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Title
Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses Yingwei Li S. Bai Cihang Xie Zhenyu A. Liao Xiaohui Shen Alan Yuille AAML 47 50 0 01 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
Variational Adversarial Active Learning Samarth Sinha Sayna Ebrahimi Trevor Darrell GAN DRL VLM SSL 39 571 0 31 Mar 2019
On the Vulnerability of CNN Classifiers in EEG-Based BCIs Xiao Zhang Dongrui Wu AAML 24 82 0 31 Mar 2019
A Provable Defense for Deep Residual Networks M. Mirman Gagandeep Singh Martin Vechev 19 26 0 29 Mar 2019
Defending against Whitebox Adversarial Attacks via Randomized Discretization Yuchen Zhang Percy Liang AAML 32 75 0 25 Mar 2019
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness J. Jacobsen Jens Behrmann Nicholas Carlini Florian Tramèr Nicolas Papernot AAML 24 46 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
Scalable Differential Privacy with Certified Robustness in Adversarial Learning Nhathai Phan My T. Thai Han Hu R. Jin Tong Sun Dejing Dou 32 14 0 23 Mar 2019
Improving Adversarial Robustness via Guided Complement Entropy Hao-Yun Chen Jhao-Hong Liang Shih-Chieh Chang Jia Pan Yu-Ting Chen Wei Wei Da-Cheng Juan AAML 6 47 0 23 Mar 2019
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes Matt Jordan Justin Lewis A. Dimakis AAML 24 57 0 20 Mar 2019
Attribution-driven Causal Analysis for Detection of Adversarial Examples Susmit Jha Sunny Raj S. Fernandes Sumit Kumar Jha S. Jha Gunjan Verma B. Jalaeian A. Swami AAML 16 17 0 14 Mar 2019
GanDef: A GAN based Adversarial Training Defense for Neural Network Classifier Guanxiong Liu Issa M. Khalil Abdallah Khreishah GAN AAML 33 19 0 06 Mar 2019
Detecting Overfitting via Adversarial Examples Roman Werpachowski András Gyorgy Csaba Szepesvári TDI 26 45 0 06 Mar 2019
Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search Abhimanyu Dubey Laurens 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
PuVAE: A Variational Autoencoder to Purify Adversarial Examples Uiwon Hwang Jaewoo Park Hyemi Jang Sungroh Yoon N. Cho AAML 15 76 0 02 Mar 2019
Aggregating explanation methods for stable and robust explainability Laura Rieger Lars Kai Hansen AAML FAtt 37 11 0 01 Mar 2019
Evaluating Adversarial Evasion Attacks in the Context of Wireless Communications Bryse Flowers R. M. Buehrer William C. Headley AAML 32 123 0 01 Mar 2019
On the Effectiveness of Low Frequency Perturbations Yash Sharma G. Ding Marcus A. Brubaker AAML 38 121 0 28 Feb 2019
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN Ke Sun Zhanxing Zhu Zhouchen Lin AAML 19 20 0 28 Feb 2019
Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors Ke Sun Zhanxing Zhu Zhouchen Lin AAML 30 18 0 28 Feb 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
Adversarial Attacks on Time Series Fazle Karim Somshubra Majumdar H. Darabi AI4TS 23 96 0 27 Feb 2019
Visualization, Discriminability and Applications of Interpretable Saak Features Abinaya Manimaran T. Ramanathan Suya You C.-C. Jay Kuo FAtt 18 8 0 25 Feb 2019
Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence Yi Han David Hubczenko Paul Montague O. Vel Tamas Abraham Benjamin I. P. Rubinstein C. Leckie T. Alpcan S. Erfani AAML 16 6 0 25 Feb 2019
Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure Fuli Feng Xiangnan He Jie Tang Tat-Seng Chua OOD AAML 34 219 0 20 Feb 2019
There are No Bit Parts for Sign Bits in Black-Box Attacks Abdullah Al-Dujaili Una-May O’Reilly AAML 21 20 0 19 Feb 2019
On Evaluating Adversarial Robustness Nicholas Carlini Anish Athalye Nicolas Papernot Wieland Brendel Jonas Rauber Dimitris Tsipras Ian Goodfellow A. Madry Alexey Kurakin ELM AAML 37 892 0 18 Feb 2019
Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces Mohammad Saidur Rahman Mohsen Imani Nate Mathews M. Wright AAML 14 80 0 18 Feb 2019
AuxBlocks: Defense Adversarial Example via Auxiliary Blocks Yueyao Yu Pengfei Yu Wenye Li AAML 14 6 0 18 Feb 2019
DeepFault: Fault Localization for Deep Neural Networks Hasan Ferit Eniser Simos Gerasimou A. Sen AAML 20 87 0 15 Feb 2019
Towards a Robust Deep Neural Network in Texts: A Survey Wenqi Wang Benxiao Tang Run Wang Lina Wang Aoshuang Ye AAML 26 39 0 12 Feb 2019
Model Compression with Adversarial Robustness: A Unified Optimization Framework Shupeng Gui Haotao Wang Chen Yu Haichuan Yang Zhangyang Wang Ji Liu MQ 13 137 0 10 Feb 2019
Minimal Images in Deep Neural Networks: Fragile Object Recognition in Natural Images S. Srivastava Guy Ben-Yosef Xavier Boix AAML 25 27 0 08 Feb 2019
Discretization based Solutions for Secure Machine Learning against Adversarial Attacks Priyadarshini Panda I. Chakraborty Kaushik Roy AAML 19 40 0 08 Feb 2019
Understanding the One-Pixel Attack: Propagation Maps and Locality Analysis Danilo Vasconcellos Vargas Jiawei Su FAtt AAML 11 36 0 08 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 Efficacy of SHIELD under Different Threat Models Cory Cornelius Nilaksh Das Shang-Tse Chen Li Chen Michael E. Kounavis Duen Horng Chau AAML 13 11 0 01 Feb 2019
A New Family of Neural Networks Provably Resistant to Adversarial Attacks Rakshit Agrawal Luca de Alfaro D. Helmbold AAML OOD 27 2 0 01 Feb 2019
Augmenting Model Robustness with Transformation-Invariant Attacks Houpu Yao Zhe Wang Guangyu Nie Yassine Mazboudi Yezhou Yang Yi Ren AAML OOD 8 3 0 31 Jan 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
Improving Adversarial Robustness of Ensembles with Diversity Training Sanjay Kariyappa Moinuddin K. Qureshi AAML FedML 17 133 0 28 Jan 2019
Defense Methods Against Adversarial Examples for Recurrent Neural Networks Ishai Rosenberg A. Shabtai Yuval Elovici Lior Rokach AAML GAN 30 42 0 28 Jan 2019
An Information-Theoretic Explanation for the Adversarial Fragility of AI Classifiers Hui Xie Jirong Yi Weiyu Xu R. Mudumbai AAML 26 3 0 27 Jan 2019
Improving Adversarial Robustness via Promoting Ensemble Diversity Tianyu Pang Kun Xu Chao Du Ning Chen Jun Zhu AAML 41 434 0 25 Jan 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 57 2,500 0 24 Jan 2019
Optimization Problems for Machine Learning: A Survey Claudio Gambella Bissan Ghaddar Joe Naoum-Sawaya AI4CE 30 178 0 16 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
Generating Adversarial Perturbation with Root Mean Square Gradient Yatie Xiao Chi-Man Pun Jizhe Zhou GAN 13 1 0 13 Jan 2019