Network Traffic Anomaly Detection Based on Dynamic Programming

Qing Yu, Xi-Wu Gu
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引用次数: 11

Abstract

In this paper, an optimum dynamic programming (DP) based time-normalization algorithm is designed for Network traffic anomaly detection. The two sets of data matched namely the sample data and the actual data, will need to calculate the time normalized distance through dynamic programming so as to achieve the effect of the anomaly detection, and have been using dynamic programming matching symmetry. By analyzing the experimental data, the traffic anomaly detection based on symmetry dynamic programming verify the improvement in the accuracy.
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基于动态规划的网络流量异常检测
本文设计了一种基于最优动态规划(DP)的网络流量异常检测时间归一化算法。对于匹配的两组数据即样本数据和实际数据,需要通过动态规划计算时间归一化距离,从而达到异常检测的效果,一直采用动态规划匹配对称。通过对实验数据的分析,验证了基于对称动态规划的流量异常检测精度的提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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