[1]YI Lei,PAN Zhisong,QIU Junyang,et al.Large-scale network traffic classification based on online learning[J].CAAI Transactions on Intelligent Systems,2016,11(3):318-327.[doi:10.11992/tis.201603033]
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Large-scale network traffic classification based on online learning

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 11 Number of periods: 2016 3 Page number: 318-327 Column: 学术论文—知识工程 Public date: 2016-06-25
Title:
Large-scale network traffic classification based on online learning
Author(s):
YI Lei;  PAN Zhisong;  QIU Junyang;  XUE Jiao;  REN Huifeng
Institute of Command Information System, PLA University of Science and Technology, Nanjing 210007, China
Keywords:
online learning; large-scale; traffic classification; timing correlation; data stream; stochastic optimization
CLC:
TP181
DOI:
10.11992/tis.201603033
Abstract:
Facing the challenges of large-scale network traffic classification problem, traditional batch machine learning algorithms suffer from slow training process and high computational complexity. In recent years, the rapid developing online learning technology is an effective way to solve large-scale problems. To address the issue of large-scale network traffic classification problem on a high-speed backbone network, we proposed a traffic classification scheme based on online learning and applied eight online learning algorithms. Experiments on real network traffic data sets showed that in the classification accuracy similar situation, online learning algorithm has less space overhead and training time than the support vector machine. Meanwhile, to examine the impact of the order of network traffic samples on the classification results, this paper compared the difference between the two ways of processing samples, sequentially and random, we verified that the presence of timing correlation in network traffic samples by comparing online learning and stochastic optimization.
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