首页> 外国专利> AUTOMATED DETECTION OF MALWARE USING TRAINED NEURAL NETWORK-BASED FILE CLASSIFIERS AND MACHINE LEARNING

AUTOMATED DETECTION OF MALWARE USING TRAINED NEURAL NETWORK-BASED FILE CLASSIFIERS AND MACHINE LEARNING

机译:使用经过训练的基于神经网络的文件分类器和机器学习来自动检测恶意软件

摘要

Automated malware detection for application file packages using machine learning (e.g., trained neural network-based classifiers) is described. A particular method includes generating, at a first device, a first feature vector based on occurrences of character n-grams corresponding to a first subset of files of multiple files of an application file package. The method includes generating, at the first device, a second feature vector based on occurrences of attributes in a second subset of files of the multiple files. The method includes sending the first feature vector and the second feature vector from the first device to a second device as inputs to a file classifier. The method includes receiving, at the first device from the second device, classification data associated with the application file package based on the first feature vector and the second feature vector. The classification data indicates whether the application file package includes malware.
机译:描述了使用机器学习(例如,受过训练的基于神经网络的分类器)对应用文件包进行的自动恶意软件检测。一种特定的方法包括在第一设备处基于与应用文件包的多个文件的文件的第一子集相对应的字符n-gram的出现来生成第一特征向量。该方法包括在第一设备处基于多个文件的文件的第二子集中的属性的出现来生成第二特征向量。该方法包括将第一特征向量和第二特征向量从第一设备发送到第二设备作为对文件分类器的输入。该方法包括在第一设备处从第二设备接收基于第一特征向量和第二特征向量与应用文件包相关联的分类数据。分类数据指示应用程序文件包是否包括恶意软件。

著录项

  • 公开/公告号US2020228559A1

    专利类型

  • 公开/公告日2020-07-16

    原文格式PDF

  • 申请/专利权人 SPARKCOGNITION INC.;

    申请/专利号US202016832718

  • 发明设计人 LUCAS MCLANE;JARRED CAPELLMAN;

    申请日2020-03-27

  • 分类号H04L29/06;G06F21/55;G06F21/56;G06N3/08;G06N3/04;

  • 国家 US

  • 入库时间 2022-08-21 11:24:54

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