Towards Deep Learning Models Resistant to Adversarial Attacks

19 June 2017

Papers citing "Towards Deep Learning Models Resistant to Adversarial Attacks"

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Title
Certified Defenses for Adversarial Patches Ping Yeh-Chiang Renkun Ni Ahmed Abdelkader Chen Zhu Christoph Studer Tom Goldstein AAML 21 171 0 14 Mar 2020
On the benefits of defining vicinal distributions in latent space Puneet Mangla Vedant Singh Shreyas Jayant Havaldar V. Balasubramanian AAML 19 3 0 14 Mar 2020
Minimum-Norm Adversarial Examples on KNN and KNN-Based Models Chawin Sitawarin David Wagner AAML 15 20 0 14 Mar 2020
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation Xiaogang Xu Hengshuang Zhao Jiaya Jia AAML 20 38 0 14 Mar 2020
When are Non-Parametric Methods Robust? Robi Bhattacharjee Kamalika Chaudhuri AAML 49 27 0 13 Mar 2020
ARAE: Adversarially Robust Training of Autoencoders Improves Novelty Detection Mohammadreza Salehi Atrin Arya Barbod Pajoum Mohammad Otoofi Amirreza Shaeiri M. Rohban Hamid R. Rabiee AAML 36 62 0 12 Mar 2020
Using an ensemble color space model to tackle adversarial examples Shreyank N. Gowda C. Yuan AAML 19 1 0 10 Mar 2020
A Survey of Adversarial Learning on Graphs Liang Chen Jintang Li Jiaying Peng Tao Xie Zengxu Cao Kun Xu Xiangnan He Zibin Zheng Bingzhe Wu AAML 24 84 0 10 Mar 2020
Manifold Regularization for Locally Stable Deep Neural Networks Charles Jin Martin Rinard AAML 28 15 0 09 Mar 2020
An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods Sanghyuk Chun Seong Joon Oh Sangdoo Yun Dongyoon Han Junsuk Choe Y. Yoo AAML OOD 350 53 0 09 Mar 2020
No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT Scans by Augmenting with Adversarial Attacks Siqi Liu A. Setio Florin-Cristian Ghesu Eli Gibson Sasa Grbic Bogdan Georgescu Dorin Comaniciu AAML OOD 44 40 0 08 Mar 2020
Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles Ranjie Duan Xingjun Ma Yisen Wang James Bailey •. A. K. Qin Yun Yang AAML 169 224 0 08 Mar 2020
Adversarial Machine Learning: Bayesian Perspectives D. Insua Roi Naveiro Víctor Gallego Jason Poulos AAML 16 18 0 07 Mar 2020
Defense against adversarial attacks on spoofing countermeasures of ASV Haibin Wu Songxiang Liu Helen Meng Hung-yi Lee AAML 98 53 0 06 Mar 2020
Exploiting Verified Neural Networks via Floating Point Numerical Error Kai Jia Martin Rinard AAML 39 34 0 06 Mar 2020
Towards Practical Lottery Ticket Hypothesis for Adversarial Training Bai Li Shiqi Wang Yunhan Jia Yantao Lu Zhenyu Zhong Lawrence Carin Suman Jana AAML 41 14 0 06 Mar 2020
Search Space of Adversarial Perturbations against Image Filters D. D. Thang Toshihiro Matsui AAML 14 1 0 05 Mar 2020
Confusing and Detecting ML Adversarial Attacks with Injected Attractors Jiyi Zhang E. Chang H. Lee AAML 32 1 0 05 Mar 2020
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization Saehyung Lee Hyungyu Lee Sungroh Yoon AAML 169 113 0 05 Mar 2020
A Closer Look at Accuracy vs. Robustness Yao-Yuan Yang Cyrus Rashtchian Hongyang R. Zhang Ruslan Salakhutdinov Kamalika Chaudhuri OOD 82 26 0 05 Mar 2020
SAM: The Sensitivity of Attribution Methods to Hyperparameters Naman Bansal Chirag Agarwal Anh Nguyen FAtt 21 0 0 04 Mar 2020
Colored Noise Injection for Training Adversarially Robust Neural Networks Evgenii Zheltonozhskii Chaim Baskin Yaniv Nemcovsky Brian Chmiel A. Mendelson A. Bronstein AAML 22 5 0 04 Mar 2020
Deep Neural Network Perception Models and Robust Autonomous Driving Systems M. Shafiee Ahmadreza Jeddi Amir Nazemi Paul Fieguth A. Wong OOD 41 15 0 04 Mar 2020
Metrics and methods for robustness evaluation of neural networks with generative models Igor Buzhinsky Arseny Nerinovsky S. Tripakis AAML 42 25 0 04 Mar 2020
Denoised Smoothing: A Provable Defense for Pretrained Classifiers Hadi Salman Mingjie Sun Greg Yang Ashish Kapoor J. Zico Kolter 45 23 0 04 Mar 2020
Double Backpropagation for Training Autoencoders against Adversarial Attack Chengjin Sun Sizhe Chen Xiaolin Huang SILM AAML 45 5 0 04 Mar 2020
Type I Attack for Generative Models Chengjin Sun Sizhe Chen Jia Cai Xiaolin Huang AAML 30 10 0 04 Mar 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 96 1,814 0 03 Mar 2020
Analyzing Accuracy Loss in Randomized Smoothing Defenses Yue Gao Harrison Rosenberg Kassem Fawaz S. Jha Justin Hsu AAML 24 6 0 03 Mar 2020
Disrupting Deepfakes: Adversarial Attacks Against Conditional Image Translation Networks and Facial Manipulation Systems Nataniel Ruiz Sarah Adel Bargal Stan Sclaroff PICV AAML 25 119 0 03 Mar 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 77 63 0 02 Mar 2020
Structured Prediction with Partial Labelling through the Infimum Loss Vivien A. Cabannes Alessandro Rudi Francis R. Bach 6 40 0 02 Mar 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 222 916 0 02 Mar 2020
Adversarial Attacks and Defenses on Graphs: A Review, A Tool and Empirical Studies Wei Jin Yaxin Li Han Xu Yiqi Wang Shuiwang Ji Charu C. Aggarwal Jiliang Tang AAML GNN 34 103 0 02 Mar 2020
Sparsity Meets Robustness: Channel Pruning for the Feynman-Kac Formalism Principled Robust Deep Neural Nets Thu Dinh Bao Wang Andrea L. Bertozzi Stanley J. Osher AAML 19 17 0 02 Mar 2020
Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models Xiao Zhang Jinghui Chen Quanquan Gu David Evans 31 17 0 01 Mar 2020
Improving Certified Robustness via Statistical Learning with Logical Reasoning Zhuolin Yang Zhikuan Zhao Wei Ping Jiawei Zhang Linyi Li ... Bojan Karlas Ji Liu Heng Guo Ce Zhang Yue Liu AAML 38 13 0 28 Feb 2020
DROCC: Deep Robust One-Class Classification Sachin Goyal Aditi Raghunathan Moksh Jain H. Simhadri Prateek Jain VLM 33 161 0 28 Feb 2020
Are L2 adversarial examples intrinsically different? Mingxuan Li Jingyuan Wang Yufan Wu AAML 14 0 0 28 Feb 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 28 6 0 28 Feb 2020
Detecting Patch Adversarial Attacks with Image Residuals Marius Arvinte Ahmed H. Tewfik S. Vishwanath AAML 17 5 0 28 Feb 2020
TSS: Transformation-Specific Smoothing for Robustness Certification Linyi Li Maurice Weber Xiaojun Xu Luka Rimanic B. Kailkhura Tao Xie Ce Zhang Yue Liu AAML 43 56 0 27 Feb 2020
On Isometry Robustness of Deep 3D Point Cloud Models under Adversarial Attacks Yue Zhao Yuwei Wu Caihua Chen A. Lim 3DPC 21 70 0 27 Feb 2020
Entangled Watermarks as a Defense against Model Extraction Hengrui Jia Christopher A. Choquette-Choo Varun Chandrasekaran Nicolas Papernot WaLM AAML 20 218 0 27 Feb 2020
Defense-PointNet: Protecting PointNet Against Adversarial Attacks Yu Zhang G. Liang Tawfiq Salem Nathan Jacobs AAML 3DPC 20 27 0 27 Feb 2020
Improving Robustness of Deep-Learning-Based Image Reconstruction Ankit Raj Y. Bresler Yue Liu OOD AAML 34 50 0 26 Feb 2020
Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization Sicheng Zhu Xiao Zhang David Evans SSL OOD 16 27 0 26 Feb 2020
Revisiting Ensembles in an Adversarial Context: Improving Natural Accuracy Aditya Saligrama Guillaume Leclerc AAML 16 1 0 26 Feb 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 47 792 0 26 Feb 2020
Randomization matters. How to defend against strong adversarial attacks Rafael Pinot Raphael Ettedgui Geovani Rizk Y. Chevaleyre Jamal Atif AAML 20 58 0 26 Feb 2020