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
Poisoning
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
Deep Learning and Open Set Malware Classification: A Survey
Authors: Jingyun Jia | Published: 2020-04-08
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies
Authors: David Enthoven, Zaid Al-Ars | Published: 2020-04-01
MetaPoison: Practical General-purpose Clean-label Data Poisoning
Authors: W. Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, Tom Goldstein | Published: 2020-04-01 | Updated: 2021-02-21
A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks
Authors: Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Abhradeep Thakurta | Published: 2020-03-26 | Updated: 2021-12-13