Method and system for detecting malicious behavioral patterns in a computer, using machine learning
US8516584B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 24, 2008 |
| Grant date | Aug 20, 2013 |
| Priority date | — |
| Expiry date | Oct 2, 2029 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F21/566
- 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. According to the proposed method, hardware and/or software parameters that can characterize known behavioral patterns in the computerized system are determined. Known malicious code samples are learned by a machine learning process, such as decision trees, Naïve Bayes, Bayesian Networks, and artificial neural networks, and the results of the machine learning process are analyzed in respect to these behavioral patterns. 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.