Machine learning-based technique for model provenance
US11797672B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 1, 2023 |
| Grant date | Oct 24, 2023 |
| Priority date | — |
| Expiry date | Jun 1, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2221/034
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Data is received that characterizes artefacts associated with each of a plurality of layers of a first machine learning model. Fingerprints are generated corresponding to each of the artefacts in each layer. The generated fingerprints can collectively form a model indicator for the first machine learning model. A second machine learning model then determines, based on the generated fingerprints, whether the first machine learning model is derived from another machine learning model. Data provided this characterization can be provided to a consuming application or process. This second machine learning model can be trained model with historical fingerprints having a known provenance classification. Related apparatus, systems, techniques and articles are also described.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.