Adversarial Machine Learning at Scale

4 November 2016

Papers citing "Adversarial Machine Learning at Scale"

50 / 530 papers shown

Title
A New Family of Neural Networks Provably Resistant to Adversarial Attacks Rakshit Agrawal Luca de Alfaro D. Helmbold AAML OOD 24 2 0 01 Feb 2019
Adversarial Metric Attack and Defense for Person Re-identification S. Bai Yingwei Li Yuyin Zhou Qizhu Li Philip Torr AAML 13 17 0 30 Jan 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty Dan Hendrycks Kimin Lee Mantas Mazeika NoLa 19 717 0 28 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
Cross-Entropy Loss and Low-Rank Features Have Responsibility for Adversarial Examples Kamil Nar Orhan Ocal S. Shankar Sastry Kannan Ramchandran AAML 19 54 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
Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers Daniel Liu Ronald Yu Hao Su 3DPC 34 165 0 10 Jan 2019
Image Super-Resolution as a Defense Against Adversarial Attacks Aamir Mustafa Salman H. Khan Munawar Hayat Jianbing Shen Ling Shao AAML SupR 21 167 0 07 Jan 2019
Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks Xiang Li Shihao Ji AAML 21 26 0 17 Dec 2018
Defending Against Universal Perturbations With Shared Adversarial Training Chaithanya Kumar Mummadi Thomas Brox J. H. Metzen AAML 18 60 0 10 Dec 2018
Learning Transferable Adversarial Examples via Ghost Networks Yingwei Li S. Bai Yuyin Zhou Cihang Xie Zhishuai Zhang Alan Yuille AAML 34 134 0 09 Dec 2018
AutoGAN: Robust Classifier Against Adversarial Attacks Blerta Lindqvist Shridatt Sugrim R. Izmailov AAML 23 7 0 08 Dec 2018
Interpretable Deep Learning under Fire Xinyang Zhang Ningfei Wang Hua Shen S. Ji Xiapu Luo Ting Wang AAML AI4CE 22 169 0 03 Dec 2018
AdVersarial: Perceptual Ad Blocking meets Adversarial Machine Learning K. Makarychev Pascal Dupré Yury Makarychev Giancarlo Pellegrino Dan Boneh AAML 29 64 0 08 Nov 2018
CAAD 2018: Iterative Ensemble Adversarial Attack Jiayang Liu Weiming Zhang Nenghai Yu AAML 22 4 0 07 Nov 2018
MixTrain: Scalable Training of Verifiably Robust Neural Networks Yue Zhang Yizheng Chen Ahmed Abdou M. Guizani AAML 19 23 0 06 Nov 2018
Exploring Connections Between Active Learning and Model Extraction Varun Chandrasekaran Kamalika Chaudhuri Irene Giacomelli Shane Walker Songbai Yan MIACV 14 157 0 05 Nov 2018
Learning to Defend by Learning to Attack Haoming Jiang Zhehui Chen Yuyang Shi Bo Dai T. Zhao 13 22 0 03 Nov 2018
Attack Graph Convolutional Networks by Adding Fake Nodes Xiaoyun Wang Minhao Cheng Joe Eaton Cho-Jui Hsieh S. F. Wu AAML GNN 27 78 0 25 Oct 2018
Exploring Adversarial Examples in Malware Detection Octavian Suciu Scott E. Coull Jeffrey Johns AAML 23 188 0 18 Oct 2018
Efficient Two-Step Adversarial Defense for Deep Neural Networks Ting-Jui Chang Yukun He Peng Li AAML 25 11 0 08 Oct 2018
Combinatorial Attacks on Binarized Neural Networks Elias Boutros Khalil Amrita Gupta B. Dilkina AAML 46 40 0 08 Oct 2018
Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks Sanghyun Hong Michael Davinroy Yigitcan Kaya S. Locke Ian Rackow Kevin Kulda Dana Dachman-Soled Tudor Dumitras MIACV 25 90 0 08 Oct 2018
Improving the Generalization of Adversarial Training with Domain Adaptation Chuanbiao Song Kun He Liwei Wang J. Hopcroft AAML OOD 14 131 0 01 Oct 2018
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network Xuanqing Liu Yao Li Chongruo Wu Cho-Jui Hsieh AAML OOD 21 171 0 01 Oct 2018
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks Kenneth T. Co Luis Muñoz-González Sixte de Maupeou Emil C. Lupu AAML 22 67 0 30 Sep 2018
On The Utility of Conditional Generation Based Mutual Information for Characterizing Adversarial Subspaces Chia-Yi Hsu Pei-Hsuan Lu Pin-Yu Chen Chia-Mu Yu AAML 30 1 0 24 Sep 2018
HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples Deqiang Li Ramesh Baral Tao Li Han Wang Qianmu Li Shouhuai Xu AAML 20 21 0 18 Sep 2018
Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction Jianguo Zhang Ji Wang Lifang He Zhao Li Philip S. Yu 21 31 0 11 Sep 2018
On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions Yusuke Tsuzuku Issei Sato AAML 16 62 0 11 Sep 2018
Certified Adversarial Robustness with Additive Noise Bai Li Changyou Chen Wenlin Wang Lawrence Carin AAML 28 341 0 10 Sep 2018
Controlling Over-generalization and its Effect on Adversarial Examples Generation and Detection Mahdieh Abbasi Arezoo Rajabi A. Mozafari R. Bobba Christian Gagné AAML 24 9 0 21 Aug 2018
Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer Hsueh-Ti Derek Liu Michael Tao Chun-Liang Li Derek Nowrouzezahrai Alec Jacobson AAML 33 13 0 08 Aug 2018
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models D. Su Huan Zhang Hongge Chen Jinfeng Yi Pin-Yu Chen Yupeng Gao VLM 20 387 0 05 Aug 2018
Adversarial Examples in Deep Learning: Characterization and Divergence Wenqi Wei Ling Liu Margaret Loper Stacey Truex Lei Yu Mehmet Emre Gursoy Yanzhao Wu AAML SILM 30 18 0 29 Jun 2018
Non-Negative Networks Against Adversarial Attacks William Fleshman Edward Raff Jared Sylvester Steven Forsyth Mark McLean AAML 27 41 0 15 Jun 2018
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks Chun-Chen Tu Pai-Shun Ting Pin-Yu Chen Sijia Liu Huan Zhang Jinfeng Yi Cho-Jui Hsieh Shin-Ming Cheng MLAU AAML 13 394 0 30 May 2018
Laplacian Networks: Bounding Indicator Function Smoothness for Neural Network Robustness Carlos Lassance Vincent Gripon Antonio Ortega AAML 24 16 0 24 May 2018
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing Jingyi Wang Jun Sun Peixin Zhang Xinyu Wang AAML 21 41 0 14 May 2018
AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning Jinyuan Jia Neil Zhenqiang Gong AAML 13 160 0 13 May 2018
Curriculum Adversarial Training Qi-Zhi Cai Min Du Chang-rui Liu D. Song AAML 19 159 0 13 May 2018
Formal Security Analysis of Neural Networks using Symbolic Intervals Shiqi Wang Kexin Pei Justin Whitehouse Junfeng Yang Suman Jana AAML 20 472 0 28 Apr 2018
VectorDefense: Vectorization as a Defense to Adversarial Examples V. Kabilan Brandon L. Morris Anh Totti Nguyen AAML 16 21 0 23 Apr 2018
Decoupled Networks Weiyang Liu Ziqiang Liu Zhiding Yu Bo Dai Rongmei Lin Yisen Wang James M. Rehg Le Song OOD 17 65 0 22 Apr 2018
ADef: an Iterative Algorithm to Construct Adversarial Deformations Rima Alaifari Giovanni S. Alberti Tandri Gauksson AAML 14 96 0 20 Apr 2018
Robustness via Deep Low-Rank Representations Amartya Sanyal Varun Kanade Philip Torr P. Dokania OOD 21 16 0 19 Apr 2018
Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations Alex Lamb Jonathan Binas Anirudh Goyal Dmitriy Serdyuk Sandeep Subramanian Ioannis Mitliagkas Yoshua Bengio OOD 34 43 0 07 Apr 2018
Security Consideration For Deep Learning-Based Image Forensics Wei-Ye Zhao Pengpeng Yang R. Ni Yao-Min Zhao Haorui Wu AAML 8 5 0 29 Mar 2018
Adversarial Defense based on Structure-to-Signal Autoencoders Joachim Folz Sebastián M. Palacio Jörn Hees Damian Borth Andreas Dengel AAML 26 31 0 21 Mar 2018
Adversarial Logit Pairing Harini Kannan Alexey Kurakin Ian Goodfellow AAML 34 624 0 16 Mar 2018