Ensemble Adversarial Training: Attacks and Defenses

19 May 2017

Dan Boneh

Papers citing "Ensemble Adversarial Training: Attacks and Defenses"

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Title
Novelty Detection Via Blurring Sung-Ik Choi Sae-Young Chung UQCV 13 36 0 27 Nov 2019
One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples Chang Xiao Changxi Zheng AAML 25 19 0 25 Nov 2019
When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks Minghao Guo Yuzhe Yang Rui Xu Ziwei Liu Dahua Lin AAML OOD 25 157 0 25 Nov 2019
Adversarial Examples Improve Image Recognition Cihang Xie Mingxing Tan Boqing Gong Jiang Wang Alan Yuille Quoc V. Le AAML 42 564 0 21 Nov 2019
Fine-grained Synthesis of Unrestricted Adversarial Examples Omid Poursaeed Tianxing Jiang Yordanos Goshu Harry Yang Serge J. Belongie Ser-Nam Lim AAML 37 13 0 20 Nov 2019
Analysis of Deep Networks for Monocular Depth Estimation Through Adversarial Attacks with Proposal of a Defense Method Junjie Hu Takayuki Okatani AAML MDE 43 15 0 20 Nov 2019
Deep Minimax Probability Machine Lirong He Ziyi Guo Kaizhu Huang Zenglin Xu AAML 25 2 0 20 Nov 2019
Poison as a Cure: Detecting & Neutralizing Variable-Sized Backdoor Attacks in Deep Neural Networks Alvin Chan Yew-Soon Ong AAML 25 42 0 19 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 21 104 0 13 Nov 2019
Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color Distance Zhengyu Zhao Zhuoran Liu Martha Larson AAML 18 142 0 06 Nov 2019
DLA: Dense-Layer-Analysis for Adversarial Example Detection Philip Sperl Ching-yu Kao Peng Chen Konstantin Böttinger AAML 19 34 0 05 Nov 2019
A Tale of Evil Twins: Adversarial Inputs versus Poisoned Models Ren Pang Hua Shen Xinyang Zhang S. Ji Yevgeniy Vorobeychik Xiaopu Luo Alex Liu Ting Wang AAML 19 2 0 05 Nov 2019
Ensembles of Locally Independent Prediction Models A. Ross Weiwei Pan Leo Anthony Celi Finale Doshi-Velez 25 31 0 04 Nov 2019
Fast-UAP: An Algorithm for Speeding up Universal Adversarial Perturbation Generation with Orientation of Perturbation Vectors Jiazhu Dai Le Shu AAML 14 3 0 04 Nov 2019
Online Robustness Training for Deep Reinforcement Learning Marc Fischer M. Mirman Steven Stalder Martin Vechev OnRL 11 40 0 03 Nov 2019
Certified Adversarial Robustness for Deep Reinforcement Learning Björn Lütjens Michael Everett Jonathan P. How AAML 22 91 0 28 Oct 2019
Spot Evasion Attacks: Adversarial Examples for License Plate Recognition Systems with Convolutional Neural Networks Yaguan Qian Daniel Ma Bin Wang Jun Pan Jiamin Wang Jian-Hai Chen Wujie Zhou Jing-Sheng Lei AAML 18 29 0 27 Oct 2019
Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training? Ali Shafahi Amin Ghiasi Furong Huang Tom Goldstein AAML 27 40 0 25 Oct 2019
Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks Alexander Levine S. Feizi AAML 6 61 0 23 Oct 2019
A Useful Taxonomy for Adversarial Robustness of Neural Networks L. Smith AAML 36 6 0 23 Oct 2019
A Fast Saddle-Point Dynamical System Approach to Robust Deep Learning Yasaman Esfandiari Aditya Balu K. Ebrahimi Umesh Vaidya N. Elia Soumik Sarkar OOD 22 3 0 18 Oct 2019
Enforcing Linearity in DNN succours Robustness and Adversarial Image Generation A. Sarkar Nikhil Kumar Gupta Raghu Sesha Iyengar AAML 16 11 0 17 Oct 2019
A New Defense Against Adversarial Images: Turning a Weakness into a Strength Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 58 101 0 16 Oct 2019
ODE guided Neural Data Augmentation Techniques for Time Series Data and its Benefits on Robustness A. Sarkar A. Raj Raghu Sesha Iyengar AAML AI4TS 34 0 0 15 Oct 2019
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks David Stutz Matthias Hein Bernt Schiele AAML 25 5 0 14 Oct 2019
Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative Models Derui Wang Wang Chaoran Li S. Wen Surya Nepal Yang Xiang AAML 13 32 0 14 Oct 2019
On Robustness of Neural Ordinary Differential Equations Hanshu Yan Jiawei Du Vincent Y. F. Tan Jiashi Feng OOD 24 138 0 12 Oct 2019
Orchestrating the Development Lifecycle of Machine Learning-Based IoT Applications: A Taxonomy and Survey Bin Qian Jie Su Z. Wen D. N. Jha Yinhao Li ... Albert Y. Zomaya Omer F. Rana Lizhe Wang Maciej Koutny R. Ranjan 28 4 0 11 Oct 2019
Adversarial Training: embedding adversarial perturbations into the parameter space of a neural network to build a robust system Shixian Wen Laurent Itti GAN AAML 19 1 0 09 Oct 2019
SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations Ali Dabouei Sobhan Soleymani Fariborz Taherkhani J. Dawson Nasser M. Nasrabadi AAML 104 19 0 08 Oct 2019
BUZz: BUffer Zones for defending adversarial examples in image classification Kaleel Mahmood Phuong Ha Nguyen Lam M. Nguyen THANH VAN NGUYEN Marten van Dijk AAML 12 6 0 03 Oct 2019
Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions He Zhao Trung Le Paul Montague O. Vel Tamas Abraham Dinh Q. Phung AAML 28 8 0 03 Oct 2019
Techniques for Adversarial Examples Threatening the Safety of Artificial Intelligence Based Systems Utku Kose SILM AAML 22 2 0 29 Sep 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 29 18 0 27 Sep 2019
Lower Bounds on Adversarial Robustness from Optimal Transport A. Bhagoji Daniel Cullina Prateek Mittal OOD OT AAML 32 92 0 26 Sep 2019
GAMIN: An Adversarial Approach to Black-Box Model Inversion Ulrich Aïvodji Sébastien Gambs Timon Ther MLAU 30 42 0 26 Sep 2019
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples Jinyuan Jia Ahmed Salem Michael Backes Yang Zhang Neil Zhenqiang Gong 33 384 0 23 Sep 2019
HAWKEYE: Adversarial Example Detector for Deep Neural Networks Jinkyu Koo Michael A. Roth S. Bagchi AAML 130 3 0 22 Sep 2019
COPYCAT: Practical Adversarial Attacks on Visualization-Based Malware Detection Aminollah Khormali Ahmed A. Abusnaina Songqing Chen Daehun Nyang Aziz Mohaisen AAML 34 28 0 20 Sep 2019
Adversarial Learning with Margin-based Triplet Embedding Regularization Yaoyao Zhong Weihong Deng AAML 28 50 0 20 Sep 2019
Training Robust Deep Neural Networks via Adversarial Noise Propagation Aishan Liu Xianglong Liu Chongzhi Zhang Hang Yu Qiang Liu Dacheng Tao AAML 27 110 0 19 Sep 2019
Robust Opponent Modeling via Adversarial Ensemble Reinforcement Learning in Asymmetric Imperfect-Information Games Macheng Shen Jonathan P. How AAML 29 19 0 18 Sep 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review Han Xu Yao Ma Haochen Liu Debayan Deb Hui Liu Jiliang Tang Anil K. Jain AAML 39 669 0 17 Sep 2019
Interpreting and Improving Adversarial Robustness of Deep Neural Networks with Neuron Sensitivity Chongzhi Zhang Aishan Liu Xianglong Liu Yitao Xu Hang Yu Yuqing Ma Tianlin Li AAML 27 19 0 16 Sep 2019
Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors Gilad Cohen Guillermo Sapiro Raja Giryes TDI 19 124 0 15 Sep 2019
Towards Model-Agnostic Adversarial Defenses using Adversarially Trained Autoencoders Pratik Vaishnavi Kevin Eykholt A. Prakash Amir Rahmati AAML 28 2 0 12 Sep 2019
An Empirical Investigation of Randomized Defenses against Adversarial Attacks Yannik Potdevin Dirk Nowotka Vijay Ganesh AAML 29 4 0 12 Sep 2019
Identifying and Resisting Adversarial Videos Using Temporal Consistency Xiaojun Jia Xingxing Wei Xiaochun Cao AAML 11 15 0 11 Sep 2019
Effectiveness of Adversarial Examples and Defenses for Malware Classification Robert Podschwadt Hassan Takabi AAML 16 11 0 10 Sep 2019
FDA: Feature Disruptive Attack Aditya Ganeshan S. VivekB. R. Venkatesh Babu AAML 34 100 0 10 Sep 2019