Cylance Inc.

Gabriel Acevedo

Matthew Wolff

Ryan Permeh

Andrew Davis

Michael Thomas Wojnowicz

John Brock

Homer Valentine Strong

Matthew Maisel

Kevin Beets

Derek A Soeder

Glenn Chisholm

Gary Golomb

Stuart McClure

Michael O'Dea

Seagen Levites

Under one aspect, a computer-implemented method includes receiving a query at a query interface about whether a computer file comprises malicious code. It is determined, using at least one machine learning sub model corresponding to a type of the computer file, whether the computer file comprises malicious code. Data characterizing the determination are provided to the query interface. Generating the sub model includes receiving computer files at a collection interface. Multiple sub populations of the computer files are generated based on respective types of the computer files, and random training and testing sets are generated from each of the sub populations. At least one sub model for each random training set is generated.

Automated systems and methods for generative multimodel multiclass classification and similarity analysis using machine learning

In one respect, there is provided a system for classifying malware. The system may include a data processor and a memory. The memory may include program code that provides operations when executed by the processor. The operations may include: providing, to a display, contextual information associated with a file to at least enable a classification of the file, when a malware classifier is unable to classify the file; receiving, in response to the providing of the contextual information, the classification of the file; and updating, based at least on the received classification of the file, the malware classifier to enable the malware classifier to classify the file. Methods and articles of manufacture, including computer program products, are also provided.

Advanced malware classification

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Irvine, CA, United States of America

Gabriel Acevedo