Using normalized confidence values for classifying mobile device behaviors
US10089582B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 14, 2015 |
| Grant date | Oct 2, 2018 |
| Priority date | — |
| Expiry date | Jan 7, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems for classifying mobile device behavior include generating a full classifier model that includes a finite state machine suitable for conversion into boosted decision stumps and/or which describes all or many of the features relevant to determining whether a mobile device behavior is benign or contributing to the mobile device's degradation over time. A mobile device may receive the full classifier model along with sigmoid parameters and use the model to generate a full set of boosted decision stumps from which a more focused or lean classifier model is generated by culling the full set to a subset suitable for efficiently determining whether mobile device behavior are benign. Results of applying the focused or lean classifier model may be normalized using a sigmoid function, with the resulting normalized result used to determine whether the behavior is benign or non-benign.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.