Efficient private vertical federated learning
US11588621B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 6, 2019 |
| Grant date | Feb 21, 2023 |
| Priority date | — |
| Expiry date | Jun 4, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L9/30
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Systems and techniques that facilitate universal and efficient privacy-preserving vertical federated learning are provided. In various embodiments, a key distribution component can distribute respective feature-dimension public keys and respective sample-dimension public keys to respective participants in a vertical federated learning framework governed by a coordinator, wherein the respective participants can send to the coordinator respective local model updates encrypted by the respective feature-dimension public keys and respective local datasets encrypted by the respective sample-dimension public keys. In various embodiments, an inference prevention component can verify a participant-related weight vector generated by the coordinator, based on which the key distribution component can distribute to the coordinator a functional feature-dimension secret key that can aggregate the encrypted respective local model updates into a sample-related weight vector. In various embodiments, the inference prevention component can verify the sample-related weight vector, based on which the key distribution component can distribute to the coordinator a functional sample-dimension secret key th…
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