Private and federated learning
US11824968B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 13, 2021 |
| Grant date | Nov 21, 2023 |
| Priority date | — |
| Expiry date | Sep 13, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L2209/42
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques regarding privacy preservation in a federated learning environment are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a plurality of machine learning components that can execute a machine learning algorithm to generate a plurality of model parameters. The computer executable components can also comprise an aggregator component that can synthesize a machine learning model based on an aggregate of the plurality of model parameters. The aggregator component can communicate with the plurality of machine learning components via a data privacy scheme that comprises a privacy process and a homomorphic encryption process in a federated learning environment.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.