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Behavioral Anomaly Detection System on Network Application Traffic from Many Sensors

机译:基于多个传感器的网络应用流量行为异常检测系统

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摘要

For a computer network in the era of big data, we discuss a behavioral anomaly detection system which makes it possible to analyze and immediately detect anomaly traffic behavior. Many sensor devices connect to the network and tend to generate their application traffic at quite a low communication rate. In order to observe necessary traffic information for traffic analysis in a short time, the monitoring system integrates traffic statistics of flows sent from devices which are considered to generate the same application. It detects anomaly traffic behavior on the basis of application analysis using NMF(Non-Negative Matrix Factorization).
机译:对于大数据时代的计算机网络,我们讨论了一种行为异常检测系统,该系统可以分析并立即检测异常流量行为。许多传感器设备连接到网络,并倾向于以相当低的通信速率生成其应用程序流量。为了在短时间内观察必要的流量信息以进行流量分析,监视系统集成了从被认为生成相同应用程序的设备发送的流量的流量统计信息。它使用NMF(非负矩阵分解)在应用程序分析的基础上检测异常流量行为。

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