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NETWORK-BASED APPROACH FOR TRAINING SUPERVISED LEARNING CLASSIFIERS

机译:基于网络的培训学习分类器的方法

摘要

A supervisory device in a network receives (810) traffic data from a security device that uses traffic signatures to assess traffic in the network. The supervisory device receives (815) traffic data from one or more distributed learning agents that use machine learning-based anomaly detection to assess traffic in the network. The supervisory device trains (820) a traffic classifier using the received traffic data from the security device and from the one or more distributed learning agents. The supervisory device deploys (825) the traffic classifier to a selected one of the one or more distributed learning agents.
机译:网络中的监管设备从安全设备接收(810)流量数据,该安全设备使用流量签名来评估网络中的流量。监控设备从一个或多个分布式学习代理接收流量数据(815),该分布式学习代理使用基于机器学习的异常检测来评估网络中的流量。监督设备使用从安全设备和从一个或多个分布式学习代理接收的交通数据来训练交通分类器(820)。监管设备将流量分类器部署(825)到一个或多个分布式学习代理中的选定一个。

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