APPLICATION EXECUTION CONTROL UTILIZING ENSEMBLE MACHINE LEARNING FOR DISCERNMENT

摘要

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.