Built-in Vulnerabilities to Imperceptible Adversarial Perturbations
Authors: Thomas Tanay, Jerone T. A. Andrews, Lewis D. Griffin | Published: 2018-06-19 | Updated: 2019-05-07
敵対的学習
Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus
Authors: William Fleshman, Edward Raff, Richard Zak, Mark McLean, Charles Nicholas | Published: 2018-06-12
Adversarial Regression with Multiple Learners
Authors: Liang Tong, Sixie Yu, Scott Alfeld, Yevgeniy Vorobeychik | Published: 2018-06-06
Detecting Adversarial Examples via Key-based Network
Authors: Pinlong Zhao, Zhouyu Fu, Ou wu, Qinghua Hu, Jun Wang | Published: 2018-06-02
Towards Robust Training of Neural Networks by Regularizing Adversarial Gradients
Authors: Fuxun Yu, Zirui Xu, Yanzhi Wang, Chenchen Liu, Xiang Chen | Published: 2018-05-23 | Updated: 2018-06-07
Constructing Unrestricted Adversarial Examples with Generative Models
Authors: Yang Song, Rui Shu, Nate Kushman, Stefano Ermon | Published: 2018-05-21 | Updated: 2018-12-02
Curriculum Adversarial Training
Authors: Qi-Zhi Cai, Min Du, Chang Liu, Dawn Song | Published: 2018-05-13
Gradient Masking Causes CLEVER to Overestimate Adversarial Perturbation Size
Authors: Ian Goodfellow | Published: 2018-04-21
Learning More Robust Features with Adversarial Training
Authors: Shuangtao Li, Yuanke Chen, Yanlin Peng, Lin Bai | Published: 2018-04-20
Adversarial Attacks Against Medical Deep Learning Systems
Authors: Samuel G. Finlayson, Hyung Won Chung, Isaac S. Kohane, Andrew L. Beam | Published: 2018-04-15 | Updated: 2019-02-04