Detecting malicious code in sections of computer files
US10169581B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 29, 2016 |
| Grant date | Jan 1, 2019 |
| Priority date | — |
| Expiry date | Apr 29, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2221/034
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A training data set for training a machine learning module is prepared by dividing normal files and malicious files into sections. Each section of a normal file is labeled as normal. Each section of a malicious file is labeled as malicious regardless of whether or not the section is malicious. The sections of the normal files and malicious files are used to train the machine learning module. The trained machine learning module is packaged as a machine learning model, which is provided to an endpoint computer. In the endpoint computer, an unknown file is divided into sections, which are input to the machine learning model to identify a malicious section of the unknown file, if any is present in the unknown file.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.