System and method of detecting malicious files using a trained machine learning model

Abstract

The present disclosure is directed to a system and method of detecting malicious files by using a trained machine learning model. The system may comprise a hardware processor configured to form at least one behavior pattern, calculate the convolution of all behavior patterns, select from a database of detection models at least two models for detection of malicious files on the basis of the behavior patterns, calculate the degree of harmfulness of a file being executed on the basis of an analysis of the convolution and the at least two models for detection of malicious files, form, on the basis of the degrees of harmfulness, a decision-making pattern, recognize the file being executed as malicious if the degree of similarity between the formulated decision-making pattern and at least one of a predetermined decision-making patterns from a database of decision-making patterns previously formulated on the basis of an analysis of malicious files, exceeds a predetermined threshold value.