Adversarial-Playground: A Visualization Suite for Adversarial Sample Generation
Authors: Andrew Norton, Yanjun Qi | Published: 2017-06-06 | Updated: 2017-06-16
モデルの頑健性保証
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation
Authors: Matthias Hein, Maksym Andriushchenko | Published: 2017-05-23 | Updated: 2017-11-05
Black-Box Attacks against RNN based Malware Detection Algorithms
Authors: Weiwei Hu, Ying Tan | Published: 2017-05-23
Ensemble Adversarial Training: Attacks and Defenses
Authors: Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian Goodfellow, Dan Boneh, Patrick McDaniel | Published: 2017-05-19 | Updated: 2020-04-26
Delving into adversarial attacks on deep policies
Authors: Jernej Kos, Dawn Song | Published: 2017-05-18
Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression
Authors: Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Li Chen, Michael E. Kounavis, Duen Horng Chau | Published: 2017-05-08
Universal Adversarial Perturbations Against Semantic Image Segmentation
Authors: Jan Hendrik Metzen, Mummadi Chaithanya Kumar, Thomas Brox, Volker Fischer | Published: 2017-04-19 | Updated: 2017-07-31
Enhancing Robustness of Machine Learning Systems via Data Transformations
Authors: Arjun Nitin Bhagoji, Daniel Cullina, Chawin Sitawarin, Prateek Mittal | Published: 2017-04-09 | Updated: 2017-11-29
Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks
Authors: Yi Han, Benjamin I. P. Rubinstein | Published: 2017-04-06 | Updated: 2017-05-25
Comment on “Biologically inspired protection of deep networks from adversarial attacks”
Authors: Wieland Brendel, Matthias Bethge | Published: 2017-04-05