Churn-aware machine learning for cybersecurity threat detection
US11568316B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 7, 2020 |
| Grant date | Jan 31, 2023 |
| Priority date | — |
| Expiry date | Jul 31, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Churn-aware training of a classifier which reduces the difference between predictions of two different models, such as a prior generation of a classification model and a subsequent generation. A second dataset of labelled data is scored on a prior generation of a classification model, wherein the prior generation was trained on a first dataset of labelled data. A subsequent generation of a classification model is trained with the second dataset of labelled data, wherein in training of the subsequent generation, weighting of at least some of the labelled data in the second dataset, such as labelled data threat yielded an incorrect classification, is adjusted based on the score of such labelled data in the prior generation.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.