Large-scale communication network behavior analysis and feature extraction using multiple motif pattern association rule mining

Authors:
Weisong He;Guangmin Hu;Xingmiao Yao
Affiliations:
Key Lab of Broadband Optical Fiber Transmission and Communication Networks, University of Electronic Science and Technology of China, Chengdu, China;Key Lab of Broadband Optical Fiber Transmission and Communication Networks, University of Electronic Science and Technology of China, Chengdu, China;Key Lab of Broadband Optical Fiber Transmission and Communication Networks, University of Electronic Science and Technology of China, Chengdu, China
Venue:
WSEAS TRANSACTIONS on COMMUNICATIONS
Year:
2009

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Abstract

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