
【国外标准】 IEEE Approved Draft Recommended Practice for Privacy and Security for Federated Machine Learning
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2025-06-05
- IEEE P2986
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This document provides recommended practices related to privacy and security for Federated Machine Learning, including security and privacy principles, defense mechanisms against non-malicious failures and examples of adversarial attacks on a Federated Machine Learning system. This document also defines an assessment framework to determine the effectiveness of a given defense mechanism under various settings.
标准号:
IEEE P2986
标准名称:
IEEE Approved Draft Recommended Practice for Privacy and Security for Federated Machine Learning
英文名称:
标准状态:
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发布日期:
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