Neural attention mechanisms for malware analysis
US9705904B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 24, 2016 |
| Grant date | Jul 11, 2017 |
| Priority date | — |
| Expiry date | Aug 24, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2221/033
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
As part of an analysis of the likelihood that a given input (e.g. a file, etc.) includes malicious code, a convolutional neural network can be used to review a sequence of chunks into which an input is divided to assess how best to navigate through the input and to classify parts of the input in a most optimal manner. At least some of the sequence of chunks can be further examined using a recurrent neural network in series with the convolutional neural network to determine how to progress through the sequence of chunks. A state of the at least some of the chunks examined using the recurrent neural network summarized to form an output indicative of the likelihood that the input includes malicious code. Methods, systems, and articles of manufacture are also described.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.