Using Randomness to Improve Robustness of Machine-Learning Models Against Evasion Attacks
Authors: Fan Yang, Zhiyuan Chen | Published: 2018-08-10
敵対的攻撃
Android HIV: A Study of Repackaging Malware for Evading Machine-Learning Detection
Authors: Xiao Chen, Chaoran Li, Derui Wang, Sheng Wen, Jun Zhang, Surya Nepal, Yang Xiang, Kui Ren | Published: 2018-08-10 | Updated: 2021-11-16
Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer
Authors: Hsueh-Ti Derek Liu, Michael Tao, Chun-Liang Li, Derek Nowrouzezahrai, Alec Jacobson | Published: 2018-08-08 | Updated: 2019-02-17
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
Security and Privacy Issues in Deep Learning
Authors: Ho Bae, Jaehee Jang, Dahuin Jung, Hyemi Jang, Heonseok Ha, Hyungyu Lee, Sungroh Yoon | Published: 2018-07-31 | Updated: 2021-03-10
Rob-GAN: Generator, Discriminator, and Adversarial Attacker
Authors: Xuanqing Liu, Cho-Jui Hsieh | Published: 2018-07-27 | Updated: 2019-04-15
Simultaneous Adversarial Training – Learn from Others Mistakes
Authors: Zukang Liao | Published: 2018-07-21 | Updated: 2018-09-10