Secure machine learning analytics using homomorphic encryption
US11196541B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 27, 2020 |
| Grant date | Dec 7, 2021 |
| Priority date | — |
| Expiry date | Mar 19, 2040 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L2209/88
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Provided are methods and systems for performing a secure machine learning analysis over an instance of data. An example method includes acquiring, by a client, an homomorphic encryption scheme, and at least one machine learning model data structure. The method further includes generating, using the encryption scheme, at least one homomorphically encrypted data structure, and sending the encrypted data structure to at least one server. The method includes executing a machine learning model, by the at least one server based on the encrypted data structure to obtain an encrypted result. The method further includes sending, by the server, the encrypted result to the client where the encrypted result is decrypted. The machine learning model includes neural networks and decision trees.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.