Membership inference vulnerabilities in peer-to-peer federated learning

Membership inference vulnerabilities in peer-to-peer federated learning

Federated learning is emerging as an efficient approach to exploit data silos that form due to regulations about data sharing and usage, thereby leveraging distributed resources to improve the learning of ML models. It is a fitting technology for cyber physical systems in applications like connected...

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Bibliographic Details
Main Authors:	Luqman, Alka, Chattopadhyay, Anupam, Lam Kwok-Yan
Other Authors:	School of Computer Science and Engineering
Format:	Conference Paper
Language:	English
Published:	2024
Subjects:	Computer and Information Science Federated Learning Neural Networks
Online Access:	https://hdl.handle.net/10356/173390

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