Applying multiple time series data mining to large-scale network traffic analysis

Minimize false positive and false negative is one of the difficult problems of network traffic analysis. This paper propose a large-scale communications network traffic feature analysis method using multiple time series data mining, analyze multiple traffic feature time series as a whole, produce valid association rules of abnormal network traffic feature, characterize the entire communication network security situation accurately. Experiment with Abilene network data verify this method.