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Applying multiple time series data mining to large-scale network traffic analysis
2008
2008 IEEE Conference on Cybernetics and Intelligent Systems
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.
doi:10.1109/iccis.2008.4670844
fatcat:ojio5mbfe5hwrdqhms3esihcrq