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Title: An Introduction to the Federated Learning Standard
With the growing concern on data privacy and security, it is undesirable to collect data from all users to perform machine learning tasks. Federated learning, a decentralized learning framework, was proposed to construct a shared prediction model while keeping owners' data on their own devices. This paper presents an introduction to the emerging federated learning standard and discusses its various aspects, including i) an overview of federated learning, ii) types of federated learning, iii) major concerns and the performance evaluation criteria of federated learning, and iv) associated regulatory requirements. The purpose of this paper is to provide an understanding of the standard and facilitate its usage in model building across organizations while meeting privacy and security concerns.  more » « less
Award ID(s):
2107190
PAR ID:
10356968
Author(s) / Creator(s):
;
Date Published:
Journal Name:
GetMobile: Mobile Computing and Communications
Volume:
25
Issue:
3
ISSN:
2375-0529
Page Range / eLocation ID:
18 to 22
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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