Systems and methods for detecting malicious network traffic using multi-domain machine learning
US12069072B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 29, 2020 |
| Grant date | Aug 20, 2024 |
| Priority date | — |
| Expiry date | Nov 20, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
System and methods for cross-domain training and updating of models to perform classification and scoring of network data/traffic are described. Information used to build deep machine learning models about traffic in one domain is used to improve the modeling in another domain. By using cross-domain learning, labeled data from another domain can be used to improve the detection rate and false positive rate of an analytic model in another domain. Because of the construction of the models, and because the models, and not the data are transferred, there is no disclosure of personally identifiable or otherwise restricted information.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.