Federated Learning
What is Federated Learning?
A machine learning approach where a model is trained across multiple decentralised devices or servers holding local data samples, without exchanging the raw data. Federated learning helps preserve data privacy while enabling collaborative model training.
Terms that appear alongside federated learning
Each of these is named in at least one of the same controls as federated learning. The number is how many controls name both.
- differential privacy 6 shared controls
- gdpr 5 shared controls
- encryption 3 shared controls
- pseudonymisation 3 shared controls
- nist 3 shared controls
- compliance 3 shared controls
- audit 3 shared controls
- data minimisation 3 shared controls
Frameworks that govern federated learning
What the standards actually require on federated learning
Requirements naming federated learning across 6 standards, quoted from the control text.
Clauses 6 + 6.1 establish ethical values elicitation and prioritisation. Per public IEEE 7000-2021 abstract + Wikipedia + academic literature (full IEEE text NOT reproduced): elicit values from stakeholders covering categories: human autonomy + beneficence + n...
IEEE7000-Values-Elicitation-Prioritisation-IEEE7000Family-Bias-Privacy-Transparency · IEEE 7000 Clauses 6 + 6.1 - Ethical Values Elicitation + Prioritisation + IEEE 7000 Family Integration (Bias + Privacy + Transparency + Wellbeing) →Privacy (Puraibasii プライバシー) is the fourth of 10 Principles per Japan AI Guidelines for Business + intersects with APPI Act on Protection of Personal Information (2022 Amendment effective April 2023) + Copyright Act 2018 Amendment Article 30-4 (text and data mi...
JP-AIG-Data-Governance-Training-Data-Quality-Provenance-Lineage-Copyright-APPI-Personal-Information-Protection · Japan AI Guidelines Data Governance + Training Data Quality + Provenance + Lineage + Copyright Act 2018 Article 30-4 Text Data Mining Exception + APPI 2022 Amendment + Personal Information Protection + Privacy Principle →Global CBPR Forum 2024-2025 status + pipeline. UK ACCESSION 2024: United Kingdom acceded April 2024 + first non-APEC member; ICO + DSIT signed accession; first wave of UK-certified Accountability Agents accredited;
CBPR-2024-2025-UK-NewJurisdictions-AI-PEP · Global CBPR Forum: 2024-2025 Update Pipeline - UK 2024, AI Integration, PEP, ASEAN MCC →Security Dimension 8 Privacy per X.805 Clause 6.8: Privacy provides protection of information that might be derived from the observation of network activities.
X805-Dim8-Privacy-Identification-Network-Activity-Personal-Information-Confidentiality · ITU-T X.805 Security Dimension 8 - Privacy + Identification of Network Activity + Personal Information Confidentiality + Subscriber Anonymity + Pseudonymity + Anti-Tracking + Location Privacy + Data Minimization + GDPR/CCPA Alignment →Section 34 of the Jamaica Data Protection Act 2020 establishes Privacy by Design + Privacy by Default + and Data Protection Impact Assessment (DPIA) requirements.
JM-DPA2020-Privacy-by-Design-Default-Sec34-Engineering-Data-Protection-Impact-Assessment-DPIA-Risk-Based · Jamaica DPA 2020 Privacy by Design + Privacy by Default + Section 34 + Data Protection Impact Assessment (DPIA) + Risk-Based + High-Risk Processing + Prior Consultation + Privacy Engineering →Section 7 of KOSA establishes a framework for qualified researcher access to covered platform data for public interest research. (1) Section 7(a) Qualified Researcher Definition: (a) Affiliated with accredited higher education institution + non-profit research...
KOSA-Researcher-Access-Section7-Qualified-Researchers-Public-Interest-Research-Approval-Process-Data-Sharing-Protections · KOSA Researcher Access + Section 7 + Qualified Researchers + Public Interest Research + Approval Process + Data Sharing + Privacy Protections + Methodology Standards + Public Reporting + Academic + Civil Society + Government Researchers →Questions people ask about federated learning
What is Federated Learning?
Why is Federated Learning important for compliance?
Which compliance frameworks address Federated Learning?
Where can I learn more about Federated Learning?
See how Federated Learning applies across compliance frameworks
Our platform maps 686 frameworks with 311K cross-framework control mappings. Explore how this concept is addressed across standards.