The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 28, 2020

Filed:

Nov. 07, 2016
Applicant:

Cylance Inc., Irvine, CA (US);

Inventors:

Xuan Zhao, Irvine, CA (US);

Matthew Wolff, Laguna Niguel, CA (US);

John Brock, Irvine, CA (US);

Brian Wallace, Irvine, CA (US);

Andrew Wortman, Irvine, CA (US);

Jian Luan, Irvine, CA (US);

Mahdi Azarafrooz, Irvine, CA (US);

Andrew Davis, Portland, OR (US);

Michael Wojnowicz, Irvine, CA (US);

Derek Soeder, Irvine, CA (US);

David Beveridge, Portland, OR (US);

Yaroslav Oliinyk, Portland, OR (US);

Ryan Permeh, Irvine, CA (US);

Assignee:

Cylance Inc., Irvine, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); G06N 3/08 (2006.01); G06F 21/55 (2013.01); G06F 21/56 (2013.01); G06N 20/10 (2019.01); G06N 3/04 (2006.01);
U.S. Cl.
CPC ...
H04L 63/1416 (2013.01); G06F 21/552 (2013.01); G06F 21/562 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06N 20/10 (2019.01);
Abstract

In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: processing a container file with a trained machine learning model, wherein the trained machine learning is trained to determine a classification for the container file indicative of whether the container file includes at least one file rendering the container file malicious; and providing, as an output by the trained machine learning model, an indication of whether the container file includes the at least one file rendering the container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.


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