Method and system for detecting malicious behavioral patterns in a computer, using machine learning
US8490194B2 · kind B2 · utility
Inventors
Key dates
| Filing date | Jan 29, 2007 |
| Grant date | Jul 16, 2013 |
| Priority date | — |
| Expiry date | Mar 12, 2030 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/048
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Method for detecting malicious behavioral patterns which are related to malicious software such as a computer worm in computerized systems that include data exchange channels with other systems over a data network. Accordingly, hardware and/or software parameters are determined in the computerized system that is can characterize known behavioral patterns thereof. Known malicious code samples are learned by a machine learning process, such as decision trees and artificial neural networks, and the results of the machine learning process are analyzed in respect to the behavioral patterns of the computerized system. Then known and unknown malicious code samples are identified according to the results of the machine learning process.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.