Improved Adversarial Training via Learned Optimizer
Authors: Yuanhao Xiong, Cho-Jui Hsieh | Published: 2020-04-25
ポイズニング
A Black-box Adversarial Attack Strategy with Adjustable Sparsity and Generalizability for Deep Image Classifiers
Authors: Arka Ghosh, Sankha Subhra Mullick, Shounak Datta, Swagatam Das, Rammohan Mallipeddi, Asit Kr. Das | Published: 2020-04-24 | Updated: 2021-09-09
Adversarial Attacks and Defenses: An Interpretation Perspective
Authors: Ninghao Liu, Mengnan Du, Ruocheng Guo, Huan Liu, Xia Hu | Published: 2020-04-23 | Updated: 2020-10-07
How to compare adversarial robustness of classifiers from a global perspective
Authors: Niklas Risse, Christina Göpfert, Jan Philip Göpfert | Published: 2020-04-22 | Updated: 2020-10-15
A Framework for Evaluating Gradient Leakage Attacks in Federated Learning
Authors: Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, Yanzhao Wu | Published: 2020-04-22 | Updated: 2020-04-23
Headless Horseman: Adversarial Attacks on Transfer Learning Models
Authors: Ahmed Abdelkader, Michael J. Curry, Liam Fowl, Tom Goldstein, Avi Schwarzschild, Manli Shu, Christoph Studer, Chen Zhu | Published: 2020-04-20
Data Poisoning Attacks on Federated Machine Learning
Authors: Gan Sun, Yang Cong, Jiahua Dong, Qiang Wang, Ji Liu | Published: 2020-04-19
Poisoning Attacks on Algorithmic Fairness
Authors: David Solans, Battista Biggio, Carlos Castillo | Published: 2020-04-15 | Updated: 2020-06-26
Weight Poisoning Attacks on Pre-trained Models
Authors: Keita Kurita, Paul Michel, Graham Neubig | Published: 2020-04-14
Towards Federated Learning With Byzantine-Robust Client Weighting
Authors: Amit Portnoy, Yoav Tirosh, Danny Hendler | Published: 2020-04-10 | Updated: 2021-05-18