Network Traffic Anomaly Detection Based on Dynamic Programming
Qìng Yu, Xiaowei Gu · 2017
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.