Ensemble Adversarial Training: Attacks and Defenses

19 May 2017

Dan Boneh

Papers citing "Ensemble Adversarial Training: Attacks and Defenses"

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Title
Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness Walt Woods Jack H Chen C. Teuscher AAML 18 46 0 07 Jun 2019
Robust Attacks against Multiple Classifiers Juan C. Perdomo Yaron Singer AAML 18 10 0 06 Jun 2019
Stochasticity and Robustness in Spiking Neural Networks W. Olin-Ammentorp K. Beckmann Catherine D. Schuman J. Plank N. Cady 25 12 0 06 Jun 2019
CANet: An Unsupervised Intrusion Detection System for High Dimensional CAN Bus Data Markus Hanselmann Thilo Strauss Katharina Dormann Holger Ulmer 12 156 0 06 Jun 2019
Multi-way Encoding for Robustness Donghyun Kim Sarah Adel Bargal Jianming Zhang Stan Sclaroff AAML 18 2 0 05 Jun 2019
RL-Based Method for Benchmarking the Adversarial Resilience and Robustness of Deep Reinforcement Learning Policies Vahid Behzadan W. Hsu AAML OffRL 13 8 0 03 Jun 2019
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models P. Morawiecki Przemysław Spurek Marek Śmieja Jacek Tabor AAML OOD 11 8 0 03 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
Are Labels Required for Improving Adversarial Robustness? J. Uesato Jean-Baptiste Alayrac Po-Sen Huang Robert Stanforth Alhussein Fawzi Pushmeet Kohli AAML 16 331 0 31 May 2019
Bandlimiting Neural Networks Against Adversarial Attacks Yuping Lin A. KasraAhmadiK. Hui Jiang AAML 6 6 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
Cross-Domain Transferability of Adversarial Perturbations Muzammal Naseer Salman H. Khan M. H. Khan Fahad Shahbaz Khan Fatih Porikli AAML 33 145 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
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 16 77 0 27 May 2019
Non-Determinism in Neural Networks for Adversarial Robustness Daanish Ali Khan Linhong Li Ninghao Sha Zhuoran Liu Abelino Jiménez Bhiksha Raj Rita Singh OOD AAML 11 3 0 26 May 2019
Purifying Adversarial Perturbation with Adversarially Trained Auto-encoders Hebi Li Qi Xiao Shixin Tian Jin Tian AAML 24 4 0 26 May 2019
Trust but Verify: An Information-Theoretic Explanation for the Adversarial Fragility of Machine Learning Systems, and a General Defense against Adversarial Attacks Jirong Yi Hui Xie Leixin Zhou Xiaodong Wu Weiyu Xu R. Mudumbai AAML 22 6 0 25 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 38 0 0 23 May 2019
A Direct Approach to Robust Deep Learning Using Adversarial Networks Huaxia Wang Chun-Nam Yu GAN AAML OOD 16 77 0 23 May 2019
Convergence and Margin of Adversarial Training on Separable Data Zachary B. Charles Shashank Rajput S. Wright Dimitris Papailiopoulos AAML 31 16 0 22 May 2019
Adversarially robust transfer learning Ali Shafahi Parsa Saadatpanah Chen Zhu Amin Ghiasi Christoph Studer David Jacobs Tom Goldstein OOD 15 114 0 20 May 2019
What Do Adversarially Robust Models Look At? Takahiro Itazuri Yoshihiro Fukuhara Hirokatsu Kataoka Shigeo Morishima 19 5 0 19 May 2019
Percival: Making In-Browser Perceptual Ad Blocking Practical With Deep Learning Z. Din P. Tigas Samuel T. King B. Livshits VLM 39 29 0 17 May 2019
Simple Black-box Adversarial Attacks Chuan Guo Jacob R. Gardner Yurong You A. Wilson Kilian Q. Weinberger AAML 22 568 0 17 May 2019
On Norm-Agnostic Robustness of Adversarial Training Bai Li Changyou Chen Wenlin Wang Lawrence Carin OOD SILM 8 7 0 15 May 2019
An Efficient Pre-processing Method to Eliminate Adversarial Effects Hua Wang Jie Wang Z. Yin AAML 14 1 0 15 May 2019
Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models M. Singh Abhishek Sinha Nupur Kumari Harshitha Machiraju Balaji Krishnamurthy V. Balasubramanian AAML 19 61 0 13 May 2019
A Comprehensive Analysis on Adversarial Robustness of Spiking Neural Networks Saima Sharmin Priyadarshini Panda Syed Shakib Sarwar Chankyu Lee Wachirawit Ponghiran Kaushik Roy AAML 24 66 0 07 May 2019
Adaptive Generation of Unrestricted Adversarial Inputs Isaac Dunn Hadrien Pouget T. Melham Daniel Kroening AAML 20 7 0 07 May 2019
Better the Devil you Know: An Analysis of Evasion Attacks using Out-of-Distribution Adversarial Examples Vikash Sehwag A. Bhagoji Liwei Song Chawin Sitawarin Daniel Cullina M. Chiang Prateek Mittal OODD 32 26 0 05 May 2019
When Attackers Meet AI: Learning-empowered Attacks in Cooperative Spectrum Sensing Z. Luo Shangqing Zhao Zhuo Lu Jie Xu Y. Sagduyu AAML 25 53 0 04 May 2019
Weight Map Layer for Noise and Adversarial Attack Robustness Mohammed Amer Tomás Maul 17 4 0 02 May 2019
NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks Yandong Li Lijun Li Liqiang Wang Tong Zhang Boqing Gong AAML 18 245 0 01 May 2019
Adversarial Training and Robustness for Multiple Perturbations Florian Tramèr Dan Boneh AAML SILM 28 375 0 30 Apr 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 68 1,231 0 29 Apr 2019
Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks Xiang He Sibei Yang Linchao Zhu Haofeng Li Huiyou Chang Yizhou Yu 9 62 0 27 Apr 2019
ZK-GanDef: A GAN based Zero Knowledge Adversarial Training Defense for Neural Networks Guanxiong Liu Issa M. Khalil Abdallah Khreishah AAML 22 18 0 17 Apr 2019
Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers Ameya Joshi Amitangshu Mukherjee S. Sarkar C. Hegde AAML 8 99 0 17 Apr 2019
Defensive Quantization: When Efficiency Meets Robustness Ji Lin Chuang Gan Song Han MQ 42 202 0 17 Apr 2019
Interpreting Adversarial Examples with Attributes Sadaf Gulshad J. H. Metzen A. Smeulders Zeynep Akata FAtt AAML 33 6 0 17 Apr 2019
AT-GAN: An Adversarial Generator Model for Non-constrained Adversarial Examples Xiaosen Wang Kun He Chuanbiao Song Liwei Wang J. Hopcroft GAN 13 32 0 16 Apr 2019
Detecting the Unexpected via Image Resynthesis Krzysztof Lis K. K. Nakka Pascal Fua Mathieu Salzmann UQCV 14 175 0 16 Apr 2019
Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks David J. Miller Zhen Xiang G. Kesidis AAML 19 35 0 12 Apr 2019
Generating Minimal Adversarial Perturbations with Integrated Adaptive Gradients Yatie Xiao Chi-Man Pun AAML GAN TTA 13 0 0 12 Apr 2019
Cycle-Consistent Adversarial GAN: the integration of adversarial attack and defense Lingyun Jiang Kai Qiao Ruoxi Qin Linyuan Wang Jian Chen Haibing Bu Bin Yan AAML 12 8 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
HopSkipJumpAttack: A Query-Efficient Decision-Based Attack Jianbo Chen Michael I. Jordan Martin J. Wainwright AAML 33 654 0 03 Apr 2019
Curls & Whey: Boosting Black-Box Adversarial Attacks Yucheng Shi Siyu Wang Yahong Han AAML 18 116 0 02 Apr 2019
Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning A. Salem Apratim Bhattacharyya Michael Backes Mario Fritz Yang Zhang FedML AAML MIACV 28 250 0 01 Apr 2019