articleIEEE Communications Surveys & TutorialsJan 1, 2008GREEN OA

A survey of techniques for internet traffic classification using machine learning

Swinburne University of Technology

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Abstract

The research community has begun looking for IP traffic classification techniques that do not rely on `well known' TCP or UDP port numbers, or interpreting the contents of packet payloads. New work is emerging on the use of statistical traffic characteristics to assist in the identification and classification process. This survey paper looks at emerging research into the application of Machine Learning (ML) techniques to IP traffic classification - an inter-disciplinary blend of IP networking and data mining techniques. We provide context and motivation for the application of ML techniques to IP traffic classification, and review 18 significant works that cover the dominant period from 2004 to early 2007.…

Citation impact

1,629
total citations
FWCI
88.70
Percentile
100%
References
71
Citations per year

Authors

2

Topics & keywords

Keywords
  • Computer science
  • Traffic classification
  • Deep packet inspection
  • Context (archaeology)
  • The Internet
  • Identification (biology)
  • Internet traffic
  • Open research
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