Towards Deep Learning Models Resistant to Adversarial Attacks

19 June 2017

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

50 / 6,508 papers shown

Title
A Dual Approach to Scalable Verification of Deep Networks Krishnamurthy Dvijotham Dvijotham Robert Stanforth Sven Gowal Timothy A. Mann Pushmeet Kohli 22 395 0 17 Mar 2018
Adversarial Logit Pairing Harini Kannan Alexey Kurakin Ian Goodfellow AAML 36 625 0 16 Mar 2018
Semantic Adversarial Examples Hossein Hosseini Radha Poovendran GAN AAML 31 196 0 16 Mar 2018
Large Margin Deep Networks for Classification Gamaleldin F. Elsayed Dilip Krishnan H. Mobahi Kevin Regan Samy Bengio MQ 22 281 0 15 Mar 2018
Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task Training Derui Wang Chaoran Li S. Wen Surya Nepal Yang Xiang AAML 33 29 0 14 Mar 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 13 503 0 13 Mar 2018
Invisible Mask: Practical Attacks on Face Recognition with Infrared Zhe Zhou Di Tang Xiaofeng Wang Weili Han Xiangyu Liu Kehuan Zhang CVBM AAML 18 103 0 13 Mar 2018
Detecting Adversarial Examples via Neural Fingerprinting Sumanth Dathathri Stephan Zheng Tianwei Yin Richard M. Murray Yisong Yue MLAU AAML 33 0 0 11 Mar 2018
Detecting Adversarial Examples - A Lesson from Multimedia Forensics Pascal Schöttle Alexander Schlögl Cecilia Pasquini Rainer Böhme AAML 14 4 0 09 Mar 2018
On Generation of Adversarial Examples using Convex Programming E. Balda Arash Behboodi R. Mathar AAML 16 13 0 09 Mar 2018
Stochastic Activation Pruning for Robust Adversarial Defense Guneet Singh Dhillon Kamyar Azizzadenesheli Zachary Chase Lipton Jeremy Bernstein Jean Kossaifi Aran Khanna Anima Anandkumar AAML 19 545 0 05 Mar 2018
Var-CNN: A Data-Efficient Website Fingerprinting Attack Based on Deep Learning Sanjit Bhat David Lu Albert Kwon S. Devadas AAML 21 190 0 28 Feb 2018
Understanding and Enhancing the Transferability of Adversarial Examples Lei Wu Zhanxing Zhu Cheng Tai E. Weinan AAML SILM 30 96 0 27 Feb 2018
Robust GANs against Dishonest Adversaries Zhi Xu Chengtao Li Stefanie Jegelka AAML 34 3 0 27 Feb 2018
On the Suitability of $L_p$ -norms for Creating and Preventing Adversarial Examples Mahmood Sharif Lujo Bauer Michael K. Reiter AAML 16 137 0 27 Feb 2018
Adversarial vulnerability for any classifier Alhussein Fawzi Hamza Fawzi Omar Fawzi AAML 30 248 0 23 Feb 2018
Deep Defense: Training DNNs with Improved Adversarial Robustness Ziang Yan Yiwen Guo Changshui Zhang AAML 38 109 0 23 Feb 2018
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries Z. Yao A. Gholami Qi Lei Kurt Keutzer Michael W. Mahoney 27 163 0 22 Feb 2018
Adversarial Examples that Fool both Computer Vision and Time-Limited Humans Gamaleldin F. Elsayed Shreya Shankar Brian Cheung Nicolas Papernot Alexey Kurakin Ian Goodfellow Jascha Narain Sohl-Dickstein AAML 39 259 0 22 Feb 2018
Adversarial Training for Probabilistic Spiking Neural Networks Alireza Bagheri Osvaldo Simeone Bipin Rajendran AAML 18 26 0 22 Feb 2018
L2-Nonexpansive Neural Networks Haifeng Qian M. Wegman 25 74 0 22 Feb 2018
Attack Strength vs. Detectability Dilemma in Adversarial Machine Learning Christopher Frederickson Michael Moore Glenn Dawson R. Polikar AAML 8 32 0 20 Feb 2018
On Lyapunov exponents and adversarial perturbation Vinay Uday Prabhu Nishant Desai John Whaley AAML 15 4 0 20 Feb 2018
Divide, Denoise, and Defend against Adversarial Attacks Seyed-Mohsen Moosavi-Dezfooli A. Shrivastava Oncel Tuzel AAML 24 45 0 19 Feb 2018
Are Generative Classifiers More Robust to Adversarial Attacks? Yingzhen Li John Bradshaw Yash Sharma AAML 57 78 0 19 Feb 2018
DARTS: Deceiving Autonomous Cars with Toxic Signs Chawin Sitawarin A. Bhagoji Arsalan Mosenia M. Chiang Prateek Mittal AAML 29 233 0 18 Feb 2018
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks J. Uesato Brendan O'Donoghue Aaron van den Oord Pushmeet Kohli AAML 22 596 0 15 Feb 2018
Fooling OCR Systems with Adversarial Text Images Congzheng Song Vitaly Shmatikov AAML 32 51 0 15 Feb 2018
Predicting Adversarial Examples with High Confidence A. Galloway Graham W. Taylor M. Moussa AAML 21 9 0 13 Feb 2018
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks Yusuke Tsuzuku Issei Sato Masashi Sugiyama AAML 35 297 0 12 Feb 2018
Certified Robustness to Adversarial Examples with Differential Privacy Mathias Lécuyer Vaggelis Atlidakis Roxana Geambasu Daniel J. Hsu Suman Jana SILM AAML 36 924 0 09 Feb 2018
Blind Pre-Processing: A Robust Defense Method Against Adversarial Examples Adnan Siraj Rakin Zhezhi He Boqing Gong Deliang Fan AAML 18 4 0 05 Feb 2018
First-order Adversarial Vulnerability of Neural Networks and Input Dimension Carl-Johann Simon-Gabriel Yann Ollivier Léon Bottou Bernhard Schölkopf David Lopez-Paz AAML 22 48 0 05 Feb 2018
Hardening Deep Neural Networks via Adversarial Model Cascades Deepak Vijaykeerthy Anshuman Suri S. Mehta Ponnurangam Kumaraguru AAML 17 10 0 02 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 60 3,157 0 01 Feb 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng Huan Zhang Pin-Yu Chen Jinfeng Yi D. Su Yupeng Gao Cho-Jui Hsieh Luca Daniel AAML 14 463 0 31 Jan 2018
Certified Defenses against Adversarial Examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 20 965 0 29 Jan 2018
Adversarial Deep Learning for Robust Detection of Binary Encoded Malware Abdullah Al-Dujaili Alex Huang Erik Hemberg Una-May O’Reilly AAML 25 186 0 09 Jan 2018
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text Nicholas Carlini D. Wagner AAML 21 1,073 0 05 Jan 2018
A General Framework for Adversarial Examples with Objectives Mahmood Sharif Sruti Bhagavatula Lujo Bauer Michael K. Reiter AAML GAN 13 191 0 31 Dec 2017
Adversarial Patch Tom B. Brown Dandelion Mané Aurko Roy Martín Abadi Justin Gilmer AAML 20 1,087 0 27 Dec 2017
The Robust Manifold Defense: Adversarial Training using Generative Models A. Jalal Andrew Ilyas C. Daskalakis A. Dimakis AAML 31 174 0 26 Dec 2017
ReabsNet: Detecting and Revising Adversarial Examples Jiefeng Chen Zihang Meng Changtian Sun Weiliang Tang Yinglun Zhu AAML GAN 16 4 0 21 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 28 1,388 0 08 Dec 2017
Generative Adversarial Perturbations Omid Poursaeed Isay Katsman Bicheng Gao Serge J. Belongie AAML GAN WIGM 31 351 0 06 Dec 2017
Towards Robust Neural Networks via Random Self-ensemble Xuanqing Liu Minhao Cheng Huan Zhang Cho-Jui Hsieh FedML AAML 38 418 0 02 Dec 2017
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training Xi Wu Uyeong Jang Jiefeng Chen Lingjiao Chen S. Jha AAML 35 21 0 21 Nov 2017
Evaluating Robustness of Neural Networks with Mixed Integer Programming Vincent Tjeng Kai Y. Xiao Russ Tedrake AAML 52 117 0 20 Nov 2017
Intriguing Properties of Adversarial Examples E. D. Cubuk Barret Zoph S. Schoenholz Quoc V. Le AAML 31 84 0 08 Nov 2017
Attacking Binarized Neural Networks A. Galloway Graham W. Taylor M. Moussa MQ AAML 14 104 0 01 Nov 2017