IEEE 2986-2023 PDF

IEEE 2986-2023 PDF

Name:
IEEE 2986-2023 PDF

Published Date:
04/26/2024

Status:
Active

Description:

IEEE Recommended Practice for Privacy and Security for Federated Machine Learning

Publisher:
IEEE

Document status:
Active

Format:
Electronic (PDF)

Delivery time:
10 minutes

Delivery time (for Russian version):
200 business days

SKU:

Choose Document Language:
$23.7
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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.
File Size : 1 file , 1.8 MB
ISBN(s) : 9798855707496, 9798855707052, 9798855707069
Note : This product is unavailable in Russia, Ukraine, Belarus
Number of Pages : 57
Product Code(s) : STD26928, STDPD26928, STDPL26940
Published : 04/26/2024

History


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