Adversarial Attacks on Node Embeddings via Graph Poisoning
Authors: Aleksandar Bojchevski, Stephan Günnemann | Published: 2018-09-04 | Updated: 2019-05-27
モデルの頑健性保証
Lipschitz regularized Deep Neural Networks generalize and are adversarially robust
Authors: Chris Finlay, Jeff Calder, Bilal Abbasi, Adam Oberman | Published: 2018-08-28 | Updated: 2019-09-12
Mitigation of Adversarial Attacks through Embedded Feature Selection
Authors: Ziyi Bao, Luis Muñoz-González, Emil C. Lupu | Published: 2018-08-16
Using Randomness to Improve Robustness of Machine-Learning Models Against Evasion Attacks
Authors: Fan Yang, Zhiyuan Chen | Published: 2018-08-10
Adversarial Vision Challenge
Authors: Wieland Brendel, Jonas Rauber, Alexey Kurakin, Nicolas Papernot, Behar Veliqi, Marcel Salathé, Sharada P. Mohanty, Matthias Bethge | Published: 2018-08-06 | Updated: 2018-12-06
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
Authors: Kaidi Xu, Sijia Liu, Pu Zhao, Pin-Yu Chen, Huan Zhang, Quanfu Fan, Deniz Erdogmus, Yanzhi Wang, Xue Lin | Published: 2018-08-05 | Updated: 2019-02-19
ATMPA: Attacking Machine Learning-based Malware Visualization Detection Methods via Adversarial Examples
Authors: Xinbo Liu, Jiliang Zhang, Yaping Lin, He Li | Published: 2018-08-05 | Updated: 2019-12-30
DeepCloak: Adversarial Crafting As a Defensive Measure to Cloak Processes
Authors: Mehmet Sinan Inci, Thomas Eisenbarth, Berk Sunar | Published: 2018-08-03 | Updated: 2020-04-23
Simultaneous Adversarial Training – Learn from Others Mistakes
Authors: Zukang Liao | Published: 2018-07-21 | Updated: 2018-09-10
Motivating the Rules of the Game for Adversarial Example Research
Authors: Justin Gilmer, Ryan P. Adams, Ian Goodfellow, David Andersen, George E. Dahl | Published: 2018-07-18 | Updated: 2018-07-20