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International Conference on Mathematical Methods, Models, and Architectures for Computer Network Security

MMM-ACNS 2017: Computer Network Security pp 223–234Cite as

A Concept of Clustering-Based Method for Botnet Detection

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Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 10446))

Abstract

The aim of this paper is to present concept of the botnet detection method based on the network flow clustering. There are a lot of botnets implementations and there are a lot of methods of their detection. Usually those methods are only effective for specific groups of botnets for example, which are using IRC, HTML or P2P protocol for internal communication. Method presented below, called BotTROP is a concept how to detect different kind of botnets based on their synchronous activity.

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Author information

Authors and Affiliations

  1. Institute of Computer and Information System, Faculty of Cybernetics, Military University of Technology, Kaliskiego Street 2, 00-908, Warsaw, Poland

    Hubert Ostap & Ryszard Antkiewicz

Authors
  1. Hubert Ostap
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  2. Ryszard Antkiewicz
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Corresponding author

Correspondence to Hubert Ostap .

Editor information

Editors and Affiliations

  1. Gdansk University of Technology , Gdansk, Poland

    Jacek Rak

  2. Binghamton University , Binghamton, New York, USA

    John Bay

  3. St. Petersburg Institute for Informatics and Automation, St. Petersburg, Russia

    Igor Kotenko

  4. Utica College , Utica, New York, USA

    Leonard Popyack

  5. Binghamton University , Binghamton, New York, USA

    Victor Skormin

  6. Warsaw University of Technology , Warsaw, Poland

    Krzysztof Szczypiorski

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© 2017 Springer International Publishing AG

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Ostap, H., Antkiewicz, R. (2017). A Concept of Clustering-Based Method for Botnet Detection. In: Rak, J., Bay, J., Kotenko, I., Popyack, L., Skormin, V., Szczypiorski, K. (eds) Computer Network Security. MMM-ACNS 2017. Lecture Notes in Computer Science(), vol 10446. Springer, Cham. https://doi.org/10.1007/978-3-319-65127-9_18

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  • DOI: https://doi.org/10.1007/978-3-319-65127-9_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65126-2

  • Online ISBN: 978-3-319-65127-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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