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The Journal of Supercomputing

, Volume 72, Issue 7, pp 2670–2681 | Cite as

An improved Hoeffding-ID data-stream classification algorithm

  • Chunyong YinEmail author
  • Lu Feng
  • Luyu Ma
Article

Abstract

Depending on the use of the Internet and network, data-stream classification has been applied in the intrusion detection field. Due to unlimited and difficult storage features, the routine classification algorithm (eg. C4.5, currently widely used classification algorithm with higher classification accuracy) tends to incorrect classification and memory leaks. In this paper, we propose an improved Hoeffding tree data-stream classification algorithm, Hoeffding-ID and apply it to the network data-stream process of the intrusion detection field. Experimental results shows that the Hoeffding-ID algorithm has relative high detection accuracy, low positives rate and memory usage not increasing with the data samples.

Keywords

Data-stream classification Hoeffding bound Intrusion detection 

Notes

Acknowledgments

Foundation item: This work was funded by the National Natural Science Foundation of China (No. 61373134). It was also supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), Jiangsu Key Laboratory of Meteorological Observation and Information Processing (No. KDXS1105) and Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET).

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.School of Computer and Software, Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Jiangsu Engineering Center of Network MonitoringNanjing University of Information Science and Technology, JiangsuNanjingChina

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