Application execution control utilizing ensemble machine learning for discernment
Application execution control utilizing ensemble machine learning for discernment
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Patent number: 10817599
Abstract: Described are techniques to enable computers to efficiently determine if they should run a program based on an immediate (i.e., real-time, etc.) analysis of the program. Such an approach leverages highly trained ensemble machine learning algorithms to create a real-time discernment on a combination of static and dynamic features collected from the program, the computer's current environment, and external factors. Related apparatus, systems, techniques and articles are also described.
Type: Grant
Filed: January 24, 2019
Date of Patent: October 27, 2020
Assignee: Cylance Inc.
Inventors: Ryan Permeh, Derek A. Soeder, Glenn Chisholm, Braden Russell, Gary Golomb, Matthew Wolff, Stuart McClure
View Patent
Patent number: 10817599
Abstract: Described are techniques to enable computers to efficiently determine if they should run a program based on an immediate (i.e., real-time, etc.) analysis of the program. Such an approach leverages highly trained ensemble machine learning algorithms to create a real-time discernment on a combination of static and dynamic features collected from the program, the computer's current environment, and external factors. Related apparatus, systems, techniques and articles are also described.
Type: Grant
Filed: January 24, 2019
Date of Patent: October 27, 2020
Assignee: Cylance Inc.
Inventors: Ryan Permeh, Derek A. Soeder, Glenn Chisholm, Braden Russell, Gary Golomb, Matthew Wolff, Stuart McClure
View Patent
Patent number: 10817599
Abstract: Described are techniques to enable computers to efficiently determine if they should run a program based on an immediate (i.e., real-time, etc.) analysis of the program. Such an approach leverages highly trained ensemble machine learning algorithms to create a real-time discernment on a combination of static and dynamic features collected from the program, the computer's current environment, and external factors. Related apparatus, systems, techniques and articles are also described.
Type: Grant
Filed: January 24, 2019
Date of Patent: October 27, 2020
Assignee: Cylance Inc.
Inventors: Ryan Permeh, Derek A. Soeder, Glenn Chisholm, Braden Russell, Gary Golomb, Matthew Wolff, Stuart McClure