Methods and systems for on-device high-granularity classification of device behaviors using multi-label models
US9910984B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 27, 2015 |
| Grant date | Mar 6, 2018 |
| Priority date | — |
| Expiry date | Oct 26, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2221/034
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Various aspects include methods and computing devices implementing the methods for evaluating device behaviors in the computing devices. Aspect methods may include using a behavior-based machine learning technique to classify a device behavior as one of benign, suspicious, and non-benign. Aspect methods may include using one of a multi-label classification and a meta-classification technique to sub-classify the device behavior into one or more sub-categories. Aspect methods may include determining a relative importance of the device behavior based on the sub-classification, and determining whether to perform robust behavior-based operations based on the determined relative importance of the device behavior.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.