Network-Level Adversaries in Federated Learning-Reference-Cited by-同舟云学术

Network-Level Adversaries in Federated Learning

Published:2022-10-03 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Conference on Communications and Network Security (CNS)
language:
Short-container-title:

Author:

Severi Giorgio¹,Jagielski Matthew²,Yar Gokberk¹,Wang Yuxuan³,Oprea Alina¹,Nita-Rotaru Cristina¹

Affiliation:

1. Northeastern University, Khoury College of Computer Sciences

2. Google Research

3. LinkedIn Corporation

Publisher

IEEE

Link

Reference43 articles.

2. On the effectiveness of mitigating data poisoning attacks with gradient shaping;hong;ArXiv,2020

3. Measuring the effects of non-identical data distribution for federated visual classification;hsu;ArXiv,2019

5. Byzantine Stochastic Gradient Descent;alistarh;NeurIPS,2018

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

2. Towards Efficient Learning on the Computing Continuum: Advancing Dynamic Adaptation of Federated Learning;Proceedings of the 14th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures;2024-06-03

3. Routing Attacks on Cryptocurrency Mining Pools;2024 IEEE Symposium on Security and Privacy (SP);2024-05-19