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
A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability Xiaowei Huang Daniel Kroening Wenjie Ruan Marta Kwiatkowska Youcheng Sun Emese Thamo Min Wu Xinping Yi AAML 24 50 0 18 Dec 2018
Spartan Networks: Self-Feature-Squeezing Neural Networks for increased robustness in adversarial settings François Menet Paul Berthier José M. Fernandez M. Gagnon AAML 10 10 0 17 Dec 2018
Perturbation Analysis of Learning Algorithms: A Unifying Perspective on Generation of Adversarial Examples E. Balda Arash Behboodi R. Mathar AAML 28 4 0 15 Dec 2018
Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing Jingyi Wang Guoliang Dong Jun Sun Xinyu Wang Peixin Zhang AAML 14 190 0 14 Dec 2018
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 55 554 0 13 Dec 2018
Thwarting Adversarial Examples: An $L_0$ -RobustSparse Fourier Transform Mitali Bafna Jack Murtagh Nikhil Vyas AAML 13 48 0 12 Dec 2018
On the Security of Randomized Defenses Against Adversarial Samples K. Sharad G. Marson H. Truong Ghassan O. Karame AAML 32 1 0 11 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 42 136 0 09 Dec 2018
Feature Denoising for Improving Adversarial Robustness Cihang Xie Yuxin Wu Laurens van der Maaten Alan Yuille Kaiming He 44 904 0 09 Dec 2018
AutoGAN: Robust Classifier Against Adversarial Attacks Blerta Lindqvist Shridatt Sugrim R. Izmailov AAML 29 7 0 08 Dec 2018
Adversarial Attacks, Regression, and Numerical Stability Regularization A. Nguyen Edward Raff AAML 13 29 0 07 Dec 2018
Fooling Network Interpretation in Image Classification Akshayvarun Subramanya Vipin Pillai Hamed Pirsiavash AAML FAtt 6 7 0 06 Dec 2018
MMA Training: Direct Input Space Margin Maximization through Adversarial Training G. Ding Yash Sharma Kry Yik-Chau Lui Ruitong Huang AAML 27 270 0 06 Dec 2018
On Configurable Defense against Adversarial Example Attacks Bo Luo Min Li Yu Li Q. Xu AAML 13 1 0 06 Dec 2018
Random Spiking and Systematic Evaluation of Defenses Against Adversarial Examples Huangyi Ge Sze Yiu Chau Bruno Ribeiro Ninghui Li AAML 27 1 0 05 Dec 2018
Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures Junhui Yin Jiayan Qiu Csaba Szepesvári Siqing Zhang Avraham Ruderman Jiyang Xie Krishnamurthy Dvijotham Zhanyu Ma N. Heess Pushmeet Kohli AAML 15 80 0 04 Dec 2018
Interpretable Deep Learning under Fire Xinyang Zhang Ningfei Wang Hua Shen S. Ji Xiapu Luo Ting Wang AAML AI4CE 30 169 0 03 Dec 2018
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 194 275 0 03 Dec 2018
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems Edward Chou Florian Tramèr Giancarlo Pellegrino AAML 182 288 0 02 Dec 2018
FineFool: Fine Object Contour Attack via Attention Jinyin Chen Haibin Zheng Hui Xiong Mengmeng Su AAML 25 3 0 01 Dec 2018
Effects of Loss Functions And Target Representations on Adversarial Robustness Sean Saito S. Roy AAML 16 7 0 01 Dec 2018
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification Qi Lei Lingfei Wu Pin-Yu Chen A. Dimakis Inderjit S. Dhillon Michael Witbrock AAML 18 92 0 01 Dec 2018
ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples Xiaojun Jia Xingxing Wei Xiaochun Cao H. Foroosh AAML 69 264 0 30 Nov 2018
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks Akhilan Boopathy Tsui-Wei Weng Pin-Yu Chen Sijia Liu Luca Daniel AAML 108 138 0 29 Nov 2018
A randomized gradient-free attack on ReLU networks Francesco Croce Matthias Hein AAML 37 21 0 28 Nov 2018
Universal Adversarial Training A. Mendrik Mahyar Najibi Zheng Xu John P. Dickerson L. Davis Tom Goldstein AAML OOD 24 189 0 27 Nov 2018
Robust Classification of Financial Risk Suproteem K. Sarkar Kojin Oshiba Daniel Giebisch Yaron Singer AAML OOD 14 14 0 27 Nov 2018
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks Jinghui Chen Dongruo Zhou Jinfeng Yi Quanquan Gu AAML 20 68 0 27 Nov 2018
ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies Bao Wang Binjie Yuan Zuoqiang Shi Stanley J. Osher AAML OOD 16 15 0 26 Nov 2018
Bilateral Adversarial Training: Towards Fast Training of More Robust Models Against Adversarial Attacks Jianyu Wang Haichao Zhang OOD AAML 32 118 0 26 Nov 2018
Noisy Computations during Inference: Harmful or Helpful? Minghai Qin D. Vučinić AAML 16 5 0 26 Nov 2018
Attention, Please! Adversarial Defense via Activation Rectification and Preservation Shangxi Wu Jitao Sang Kaiyuan Xu Jiaming Zhang Jian Yu AAML 6 7 0 24 Nov 2018
Robustness via curvature regularization, and vice versa Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi J. Uesato P. Frossard AAML 29 318 0 23 Nov 2018
Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses Jérôme Rony L. G. Hafemann Luiz Eduardo Soares de Oliveira Ismail Ben Ayed R. Sabourin Eric Granger AAML 9 297 0 23 Nov 2018
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack Adnan Siraj Rakin Zhezhi He Deliang Fan AAML 13 287 0 22 Nov 2018
Strength in Numbers: Trading-off Robustness and Computation via Adversarially-Trained Ensembles Edward Grefenstette Robert Stanforth Brendan O'Donoghue J. Uesato G. Swirszcz Pushmeet Kohli AAML 36 18 0 22 Nov 2018
Task-generalizable Adversarial Attack based on Perceptual Metric Muzammal Naseer Salman H. Khan Shafin Rahman Fatih Porikli AAML 21 39 0 22 Nov 2018
MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense Rushil Anirudh Jayaraman J. Thiagarajan B. Kailkhura T. Bremer GAN 8 2 0 20 Nov 2018
Intermediate Level Adversarial Attack for Enhanced Transferability Qian Huang Zeqi Gu Isay Katsman Horace He Pian Pawakapan Zhiqiu Lin Serge J. Belongie Ser-Nam Lim AAML SILM 11 4 0 20 Nov 2018
Lightweight Lipschitz Margin Training for Certified Defense against Adversarial Examples Hajime Ono Tsubasa Takahashi Kazuya Kakizaki AAML 16 4 0 20 Nov 2018
Optimal Transport Classifier: Defending Against Adversarial Attacks by Regularized Deep Embedding Yao Li Martin Renqiang Min Wenchao Yu Cho-Jui Hsieh T. C. Lee E. Kruus OT 24 7 0 19 Nov 2018
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 34 397 0 19 Nov 2018
Generalizable Adversarial Training via Spectral Normalization Farzan Farnia Jesse M. Zhang David Tse OOD AAML 45 138 0 19 Nov 2018
A Statistical Approach to Assessing Neural Network Robustness Stefan Webb Tom Rainforth Yee Whye Teh M. P. Kumar AAML 11 81 0 17 Nov 2018
A note on hyperparameters in black-box adversarial examples Jamie Hayes AAML MLAU 14 0 0 15 Nov 2018
A Spectral View of Adversarially Robust Features Shivam Garg Vatsal Sharan B. Zhang Gregory Valiant AAML 14 21 0 15 Nov 2018
Mathematical Analysis of Adversarial Attacks Zehao Dou Stanley J. Osher Bao Wang AAML 24 18 0 15 Nov 2018
Verification of Recurrent Neural Networks Through Rule Extraction Qinglong Wang Kaixuan Zhang Xue Liu C. Lee Giles AAML 28 18 0 14 Nov 2018
Sorting out Lipschitz function approximation Cem Anil James Lucas Roger C. Grosse 30 318 0 13 Nov 2018