A black-box adversarial attack for poisoning clustering
Authors: Antonio Emanuele Cinà, Alessandro Torcinovich, Marcello Pelillo | Published: 2020-09-09 | Updated: 2021-11-10
ポイズニング
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning
Authors: Mohammad Naseri, Jamie Hayes, Emiliano De Cristofaro | Published: 2020-09-08 | Updated: 2022-05-27
Detection Defense Against Adversarial Attacks with Saliency Map
Authors: Dengpan Ye, Chuanxi Chen, Changrui Liu, Hao Wang, Shunzhi Jiang | Published: 2020-09-06
Improving Resistance to Adversarial Deformations by Regularizing Gradients
Authors: Pengfei Xia, Bin Li | Published: 2020-08-29 | Updated: 2020-10-06
Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning
Authors: Yinghua Zhang, Yangqiu Song, Jian Liang, Kun Bai, Qiang Yang | Published: 2020-08-25
Defending Distributed Classifiers Against Data Poisoning Attacks
Authors: Sandamal Weerasinghe, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie | Published: 2020-08-21
Defending Regression Learners Against Poisoning Attacks
Authors: Sandamal Weerasinghe, Sarah M. Erfani, Tansu Alpcan, Christopher Leckie, Justin Kopacz | Published: 2020-08-21
Toward Smart Security Enhancement of Federated Learning Networks
Authors: Junjie Tan, Ying-Chang Liang, Nguyen Cong Luong, Dusit Niyato | Published: 2020-08-19
WAFFLE: Watermarking in Federated Learning
Authors: Buse Gul Atli, Yuxi Xia, Samuel Marchal, N. Asokan | Published: 2020-08-17 | Updated: 2021-07-22
Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection
Authors: Luca Demetrio, Scott E. Coull, Battista Biggio, Giovanni Lagorio, Alessandro Armando, Fabio Roli | Published: 2020-08-17 | Updated: 2021-03-22