IEEE 2986-2023

Detail information

Designation: IEEE 2986-2023

Publication date: 26/04/2024

Pages: 57

Country: International technical standard

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Anotation

New IEEE Standard - Active.
Privacy and security issues pose great challenges to the federated machine leaning (FML) community. A general view on privacy and security risks while meeting applicable privacy and security requirements in FML is provided. This recommended practice is provided in four parts: malicious failure and non-malicious failure in FML, privacy and security requirements from the perspective of system and FML participants, defensive methods and fault recovery methods, and the privacy and security risks evaluation. It also provides some guidance for typical FML scenarios in different industry areas, which can facilitate practitioners to use FML in a better way.

ISBN: 979-8-8557-0705-2, 979-8-8557-0706-9
Number of Pages: 57
Product Code: STD26928, STDPD26928
Keywords: federated machine learning, FML, IEEE 2986™, machine learning, privacy, security
Category: Computer Security and Privacy