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Data Mining and Information Security

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Computer Network Security (MMM-ACNS 2017)

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

Abstract

Analysis of information security monitoring data is based on detection of anomalies causalities in “normal” process of an information system operation.

In the paper the JSM-method of data mining in the solution of this task is considered. For this purpose in identical situations the objects generated by “normal” data and anomalies are built. Further these objects are researched by JSM-method as the positive and negative examples of anomalies appearance.

The causalities of anomalies appearance found by JSM-method can be used as signatures for fast determination of information security violations.

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Acknowledgements

The research is supported by Russian Foundation for Basic Research (project 15-29-07981).

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Authors and Affiliations

  1. Institute of Informatics Problems of Federal Research Center, “Informatics and Control” of the Russian Academy of Sciences, Vavilova 44-2, 119333, Moscow, Russia

    Alexander Grusho

Authors
  1. Alexander Grusho
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Correspondence to Alexander Grusho .

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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Grusho, A. (2017). Data Mining and Information Security. 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_3

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  • DOI: https://doi.org/10.1007/978-3-319-65127-9_3

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  • 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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