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Network security threat detection by user/user-entity behavioral analysis

机译:通过用户/用户实体行为分析检测网络安全威胁

摘要

A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.
机译:安全平台采用各种技术和机制来检测计算机网络环境中与安全相关的异常和威胁。该安全平台由“大数据”驱动,并使用机器学习来执行安全分析。安全平台执行用户/实体行为分析(UEBA),以检测与安全相关的异常和威胁,而不管以前是否知道此类异常/威胁。该安全平台可以包括用于检测异常和威胁的实时路径和批处理路径/模式。通过直观地显示带有风险等级和支持证据的分析结果,该安全平台使网络安全管理员能够对检测到的异常或威胁做出响应,并迅速采取行动。

著录项

  • 公开/公告号US9609009B2

    专利类型

  • 公开/公告日2017-03-28

    原文格式PDF

  • 申请/专利权人 SPLUNK INC.;

    申请/专利号US201615335250

  • 发明设计人 SUDHAKAR MUDDU;CHRISTOS TRYFONAS;

    申请日2016-10-26

  • 分类号H04L29/06;G06N99;

  • 国家 US

  • 入库时间 2022-08-21 13:42:11

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