An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies

1 April 2020

Papers citing "An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies"

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Title
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 20 9 0 19 Dec 2021
FedLess: Secure and Scalable Federated Learning Using Serverless Computing Andreas Grafberger Mohak Chadha Anshul Jindal Jianfeng Gu Michael Gerndt 36 49 0 05 Nov 2021
DFL: High-Performance Blockchain-Based Federated Learning Yongding Tian Zhuoran Guo Jiaxuan Zhang Zaid Al-Ars OOD FedML 29 10 0 28 Oct 2021
Fidel: Reconstructing Private Training Samples from Weight Updates in Federated Learning David Enthoven Zaid Al-Ars FedML 55 14 0 01 Jan 2021
Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins? Jeremy Georges-Filteau Elisa Cirillo SyDa AI4CE 30 17 0 27 May 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 193 434 0 04 Mar 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 179 1,032 0 29 Nov 2018
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,634 0 03 Jul 2012