首页> 外国专利> SYSTEM AND METHOD OF IDENTIFYING MALICIOUS FILES USING A LEARNING MODEL TRAINED ON A MALICIOUS FILE

SYSTEM AND METHOD OF IDENTIFYING MALICIOUS FILES USING A LEARNING MODEL TRAINED ON A MALICIOUS FILE

机译:使用在恶意文件上训练的学习模型来识别恶意文件的系统和方法

摘要

Disclosed herein are systems and methods of identifying malicious files using a learning model trained on a malicious file. In one aspect, an exemplary method comprises selecting, using a hardware processor, the malicious file from a plurality of malicious files that are known to be harmful, selecting, using the hardware processor, a plurality of safe files from a set of safe files that are known to be safe, generating, using the hardware processor, a learning model by training a neural network with the malicious file and the plurality of safe files, generating, using the hardware processor, rules for detection of malicious files from the learning model, determining, using the hardware processor, whether attributes of an unknown file fulfill the rules for detection of malicious files using the learning model and responsive to determining that the rules for detection are fulfilled, identifying, using the hardware processor, the unknown file as malicious.
机译:本文公开了使用在恶意文件上训练的学习模型来识别恶意文件的系统和方法。在一个方面,一种示例性方法包括:使用硬件处理器,从多个已知有害的恶意文件中选择恶意文件;使用该硬件处理器,从一组安全文件中选择多个安全文件,其中,已知是安全的,使用硬件处理器通过训练带有恶意文件和多个安全文件的神经网络来生成学习模型,并使用硬件处理器生成用于从学习模型中检测恶意文件的规则,使用硬件处理器确定未知文件的属性是否满足使用学习模型的恶意文件检测规则,并响应于确定检测规则得到满足,使用硬件处理器将未知文件识别为恶意文件。

著录项

  • 公开/公告号US2020004961A1

    专利类型

  • 公开/公告日2020-01-02

    原文格式PDF

  • 申请/专利权人 AO KASPERSKY LAB;

    申请/专利号US201816185270

  • 发明设计人 SERGEY V. PROKUDIN;ALEXEY M. ROMANENKO;

    申请日2018-11-09

  • 分类号G06F21/56;G06N3/08;

  • 国家 US

  • 入库时间 2022-08-21 11:20:36

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号