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Adaptive behavioral intrusion detection systems and methods

机译:自适应行为入侵检测系统和方法

摘要

Systems and methods for analyzing historical network traffic and determining which traffic does not belong in a network are disclosed. Intrusion detection is performed over a period of time, looking for behavioral patterns within networks or information systems and generating alerts when these patterns change. The intrusion detection system intelligently forms correlations between disparate sources to find traffic anomalies. Over time, behaviors are predictive, and the intrusion detection system attempts to predict outcomes, becoming proactive instead of just reactive. Intrusions occur throughout whole information systems, including both network infrastructure and application servers. By treating the information system as a whole and performing intrusion detection across it, the chances of detection are increased significantly.
机译:公开了用于分析历史网络流量并确定哪些流量不属于网络的系统和方法。入侵检测会在一段时间内执行,以查找网络或信息系统内的行为模式,并在这些模式发生变化时生成警报。入侵检测系统可以智能地在不同来源之间形成关联,以发现流量异常。随着时间的流逝,行为是可预测的,入侵检测系统会尝试预测结果,从而变得主动而不是被动。入侵发生在整个信息系统中,包括网络基础结构和应用程序服务器。通过将信息系统视为一个整体并对其进行入侵检测,可以大大提高检测机会。

著录项

  • 公开/公告号US8448247B2

    专利类型

  • 公开/公告日2013-05-21

    原文格式PDF

  • 申请/专利权人 MICHAEL STUTE;

    申请/专利号US201213453879

  • 发明设计人 MICHAEL STUTE;

    申请日2012-04-23

  • 分类号G06F21/00;

  • 国家 US

  • 入库时间 2022-08-21 16:44:59

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