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SYSTEM AND METHOD OF MACHINE LEARNING OF MALWARE DETECTION MODEL

机译:恶意软件检测模型的机器学习系统和方法

摘要

Disclosed are systems and methods for machine learning of a model for detecting malicious files. The described system samples files from a database of files and trains a detection model for detecting malicious files on the basis of an analysis of the sampled files. The described system forms behavior logs based on executable commands intercepted during execution of the sampled files, and generates behavior patterns based on the behavior log. The described system determines a convolution function based on the behavior patterns, and trains a detection model for detecting malicious files by calculating parameters of the detection model using the convolution function on the behavior patterns. The trained detection model may be used to detect malicious files by utilizing the detection model on a system behavior log generated during execution of suspicious files.
机译:公开了用于机器学习用于检测恶意文件的模型的系统和方法。所描述的系统从文件数据库中采样文件,并基于对采样文件的分析来训练用于检测恶意文件的检测模型。所描述的系统基于在采样文件的执行期间截获的可执行命令来形成行为日志,并基于行为日志生成行为模式。所描述的系统基于行为模式来确定卷积函数,并且通过使用行为模式上的卷积函数来计算检测模型的参数,来训练用于检测恶意文件的检测模型。通过在可疑文件执行期间生成的系统行为日志上利用检测模型,可以使用经过训练的检测模型来检测恶意文件。

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