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A novel method of network traffic anomaly detection

机译:一种新的网络流量异常检测方法

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摘要

The purpose of this paper is to propose a new algorithm which is based on combining the linear model and the method about smooth exponential. It is used to simulate the AR model of the Single sliding window sequence of observations and gets the average value of the square of slide window observed values' residual noise and achieve the previous statistics on the latter statistic forecast with exponential smoothing method so as to decide whether the network traffic is normal or not. This algorithm is more efficiently comparing with GLR method and more reliable comparing with smooth exponential method, and has been proved is effectively in the detection for network traffic anomalies.
机译:本文的目的是提出一种新的算法,该算法基于结合线性模型和关于平滑指数的方法。它用于模拟单个滑动窗口的观测序列的AR模型,并获得幻灯片窗口平方的平均值观察到的值的剩余噪声,并通过指数平滑方法实现后一统计预测的先前统计数据,以便决定网络流量是否正常。该算法与GLR方法更有效地比较,与平滑指数方法更加可靠地比较,并且已被证明在网络流量异常的检测中有效。

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