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Device and Network Classification Based on Probabilistic Model

机译:基于概率模型的设备和网络分类

摘要

Programmatic mechanisms that enable the automatic assignment of categories to network entities based on observed evidence. Agents gather observation data that identifies observations made by agents about the network and a plurality of nodes of the network. The agents provide the observation data to a classification module, which assigns a device category to the nodes of the network based on the observation data and a probabilistic node model. The probabilistic node model considers several probabilities to ascertain a recommended device category for a particular node, such as probabilities based on a manufacturer of a node, an operating system executing on a node, information about other nodes in the local vicinity of a node, and an administrator web page associated with a node. The classification module may also assign a particular network category to the network based on the observation data and a probabilistic network model.
机译:程序机制,可根据观察到的证据自动将类别分配给网络实体。代理收集观察数据,该数据标识由代理对网络和网络的多个节点进行的观察。代理将观察数据提供给分类模块,分类模块根据观察数据和概率节点模型将设备类别分配给网络的节点。概率节点模型考虑了为特定节点确定推荐设备类别的几种概率,例如基于节点制造商,在节点上执行的操作系统,关于节点本地附近的其他节点的信息的概率,以及与节点关联的管理员网页。分类模块还可基于观察数据和概率网络模型将特定的网络类别分配给网络。

著录项

  • 公开/公告号US2018048534A1

    专利类型

  • 公开/公告日2018-02-15

    原文格式PDF

  • 申请/专利权人 BALBIX INC.;

    申请/专利号US201715473418

  • 申请日2017-03-29

  • 分类号H04L12/24;G06N7;

  • 国家 US

  • 入库时间 2022-08-21 13:03:18

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