Privacy-preserving system for machine-learning training data
US10601786B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 2, 2018 |
| Grant date | Mar 24, 2020 |
| Priority date | — |
| Expiry date | Dec 1, 2038 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L2209/42
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
The disclosed embodiments relate to a system that anonymizes sensor data to facilitate machine-learning training operations without disclosing an associated user's identity. During operation, the system receives encrypted sensor data at a gateway server, wherein the encrypted sensor data includes a client identifier corresponding to an associated user or client device. Next, the system moves the encrypted sensor data into a secure enclave. The secure enclave then: decrypts the encrypted sensor data; replaces the client identifier with an anonymized identifier to produce anonymized sensor data; and communicates the anonymized sensor data to a machine-learning system. Finally, the machine-learning system: uses the anonymized sensor data to train a model to perform a recognition operation, and uses the trained model to perform the recognition operation on subsequently received sensor data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.