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METHODS AND APPARATUS TO IMPROVE DETECTION OF MALWARE BASED ON ECOSYSTEM SPECIFIC DATA

机译:基于生态系统特定数据改善恶意软件检测的方法和装置

摘要

Methods, apparatus, systems, and articles of manufacture are disclosed that improve detection of malware based on ecosystem specific data. An example apparatus includes a feedback weight controller to apply, with a machine learning model, a weight to feedback associated with a sample, the feedback obtained from at least a customer ecosystem and including endpoint feedback, human feedback, infrastructure feedback, and global feedback; and a sample conviction controller to, in response to a score based on the weighted feedback satisfying a threshold for a classification, indicate to a user, with the machine learning model, that the classification for the sample is malicious.
机译:公开了方法,装置,系统和制品,从而改善了基于生态系统特定数据的恶意软件的检测。 一个示例装置包括用于应用与样本相关联的机器学习模型的反馈权重控制器,其重量是与样本相关联的反馈,从至少客户生态系统获得的反馈,包括端点反馈,人的反馈,基础设施反馈和全局反馈; 和一个样本定罪控制器,响应于基于满足分类阈值的加权反馈的分数,向用户提供机器学习模型的分数,样本的分类是恶意的。

著录项

  • 公开/公告号US2021406613A1

    专利类型

  • 公开/公告日2021-12-30

    原文格式PDF

  • 申请/专利权人 MCAFEE LLC;

    申请/专利号US202016917497

  • 申请日2020-06-30

  • 分类号G06K9/62;G06F21/56;G06N20;

  • 国家 US

  • 入库时间 2022-08-24 23:07:29

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