Intriguing Properties of Adversarial Examples
Authors: Ekin D. Cubuk, Barret Zoph, Samuel S. Schoenholz, Quoc V. Le | Published: 2017-11-08
敵対的サンプル
Adversarial Frontier Stitching for Remote Neural Network Watermarking
Authors: Erwan Le Merrer, Patrick Perez, Gilles Trédan | Published: 2017-11-06 | Updated: 2019-08-07
Attacking Binarized Neural Networks
Authors: Angus Galloway, Graham W. Taylor, Medhat Moussa | Published: 2017-11-01 | Updated: 2018-01-31
One pixel attack for fooling deep neural networks
Authors: Jiawei Su, Danilo Vasconcellos Vargas, Sakurai Kouichi | Published: 2017-10-24 | Updated: 2019-10-17
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples
Authors: Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh | Published: 2017-09-13 | Updated: 2018-02-10
Learning Universal Adversarial Perturbations with Generative Models
Authors: Jamie Hayes, George Danezis | Published: 2017-08-17 | Updated: 2018-01-05
Adversarial-Playground: A Visualization Suite Showing How Adversarial Examples Fool Deep Learning
Authors: Andrew P. Norton, Yanjun Qi | Published: 2017-08-01
NO Need to Worry about Adversarial Examples in Object Detection in Autonomous Vehicles
Authors: Jiajun Lu, Hussein Sibai, Evan Fabry, David Forsyth | Published: 2017-07-12
Towards Deep Learning Models Resistant to Adversarial Attacks
Authors: Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu | Published: 2017-06-19 | Updated: 2019-09-04
Extending Defensive Distillation
Authors: Nicolas Papernot, Patrick McDaniel | Published: 2017-05-15