Framework for classifying an object as malicious with machine learning for deploying updated predictive models
US10902117B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 29, 2019 |
| Grant date | Jan 26, 2021 |
| Priority date | — |
| Expiry date | Jul 29, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/1425
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
According to one embodiment, a computerized method for acquiring updated predictive model is described. The updated predictive model is achieved through machine learning analyses of information by a training engine, which issues a control message in response to a discrepancy in a determination of the suspect object as malicious or non-malicious by a detection engine and a classification engine. The detection engine analyzes a content of a suspect object to determine whether the suspect object is malicious or non-malicious. Similarly, the classification engine analyses the suspect object based on the predictive model to determine whether the suspect object is malicious or non-malicious. The control message causes the training engine to update the predictive model based on machine learning analyses of information provided via the control message and to return an updated predictive model to the classification engine.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.