Automated systems and methods for generative multimodel multiclass classification and similarity analysis using machine learning
Automated systems and methods for generative multimodel multiclass classification and similarity analysis using machine learning
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Patent number: 11657317
Abstract: 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.
Type: Grant
Filed: October 20, 2017
Date of Patent: May 23, 2023
Assignee: Cylance Inc.
Inventors: Ryan Permeh, Stuart McClure, Matthew Wolff, Gary Golomb, Derek A. Soeder, Seagen Levites, Michael O'Dea, Gabriel Acevedo, Glenn Chisholm
View Patent
Patent number: 11657317
Abstract: 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.
Type: Grant
Filed: October 20, 2017
Date of Patent: May 23, 2023
Assignee: Cylance Inc.
Inventors: Ryan Permeh, Stuart McClure, Matthew Wolff, Gary Golomb, Derek A. Soeder, Seagen Levites, Michael O'Dea, Gabriel Acevedo, Glenn Chisholm
View Patent
Patent number: 11657317
Abstract: 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.
Type: Grant
Filed: October 20, 2017
Date of Patent: May 23, 2023
Assignee: Cylance Inc.
Inventors: Ryan Permeh, Stuart McClure, Matthew Wolff, Gary Golomb, Derek A. Soeder, Seagen Levites, Michael O'Dea, Gabriel Acevedo, Glenn Chisholm