System and method for improved end-to-end cybersecurity machine learning and deployment
US11227047B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 30, 2018 |
| Grant date | Jan 18, 2022 |
| Priority date | — |
| Expiry date | Jun 1, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The presently disclosed subject matter includes an apparatus that receives a dataset with values associated with different digital resources captured from a group of compute devices. The apparatus includes a feature extractor, to generate a set of feature vectors, each feature vector from the set of feature vectors associated with a set of data included in the received dataset. The apparatus uses the set of feature vectors to validate multiple machine learning models trained to determine whether a digital resource is associated with a cyberattack. The apparatus selects at least one active machine learning model and sets the remaining trained machine learning models to operate in an inactive mode. The active machine learning model generates a signal to alert a security administrator, blocks a digital resource from loading at a compute device, or executes other remedial action, upon a determination that the digital resource is associated with a cyberattack.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.