Analyze Large-scale Communication Network Behavior Through Mining TCP Control Segment Information
One difficult task when managing large-scale network traffic flows is that the network operators must deal with a very large number of flow records. In this paper, we introduce a new defined TCP flags information analysis method, proportion-based analysis, which is a better way to narrow the analyzable flow records. We compute the percentage of different type of TCP flags among total traffic flows and consider these as multivariate time series over a duration of time. Furthermore, we may obtain frequent pattern of different type of TCP flags using multivariate time series association rule mining method. Experimental results with backbone network (Internet2) data confirmed our method.
Weisong He Guangmin Hu
School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu, SC 610054, P.R.China
国际会议
2009国际通信电路与系统学术会议(ICCCAS 2009)(2009 International Conference on Communications，Circuits and Systems)
成都
英文
314-317
2009-07-23（万方平台首次上网日期，不代表论文的发表时间）