Prudent ensemble models in machine learning with high precision for use in network security
US11669779B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 5, 2019 |
| Grant date | Jun 6, 2023 |
| Priority date | — |
| Expiry date | Mar 13, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods include receiving a content item between a user device and a location on the Internet or an enterprise network; utilizing a trained machine learning ensemble model to determine whether the content item is malicious; responsive to the trained machine learning ensemble model determining the content item is malicious or determining the content item is benign but such determining is in a blind spot of the trained ensemble model, performing further processing on the content item; and, responsive to the trained machine learning ensemble model determining the content item is benign with such determination not in a blind spot of the trained machine learning ensemble model, allowing the content item. A blind spot is a location where the trained machine learning ensemble model has not seen any examples with a combination of features at the location or has examples with conflicting labels.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.