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Spatial and temporal convolution networks for system calls based process monitoring

机译:时空卷积网络,用于基于系统调用的过程监视

摘要

The systems and methods that detect a malicious process using count vectors are provided. Count vectors store a number and types of system calls that a process executed in a configurable time interval. The count vectors are provided to a temporal convolution network and a spatial convolution network. The temporal convolution network generates a temporal output by passing the count vectors through temporal filters that identify temporal features of the process. The spatial convolution network generates a spatial output by passing the count vectors through spatial filters that identify spatial features of the process. The temporal output and the spatial output are merged into a summary representation of the process. The malware detection system uses the summary representation to determine that the process as a malicious process.
机译:提供了使用计数向量检测恶意进程的系统和方法。计数向量存储系统调用的数量和类型,系统调用在可配置的时间间隔内执行。计数向量被提供给时间卷积网络和空间卷积网络。时间卷积网络通过将计数向量传递到识别过程的时间特征的时间滤波器来生成时间输出。空间卷积网络通过将计数向量传递到标识过程的空间特征的空间滤波器来生成空间输出。时间输出和空间输出合并为过程的摘要表示。恶意软件检测系统使用摘要表示将进程确定为恶意进程。

著录项

  • 公开/公告号AU2018390542A1

    专利类型

  • 公开/公告日2020-07-02

    原文格式PDF

  • 申请/专利权人 PAYPAL INC.;

    申请/专利号AU20180390542

  • 发明设计人 DYMSHITS MICHAEL;MYARA BENJAMIN HILLEL;

    申请日2018-12-17

  • 分类号G06F21/55;G06F7/02;G06K9;G06K9/62;

  • 国家 AU

  • 入库时间 2022-08-21 11:12:11

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