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Conceptual Data Modeling Using Aggregates to Ensure Large-Scale Distributed Data Management Systems Security

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Intelligent Distributed Computing XIII (IDC 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 868))

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Abstract

To define a common data security policy in a large-scale distributed data management system, it is necessary to create a uniform data catalog. The existing conceptual data models and their suitability for the problem are considered in the paper. The authors propose a new aggregate model for conceptual big data description in large-scale distributed data management systems security subsystems. The paper presents the mapping of the DBMS data models to the new conceptual model.

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Acknowledgements

The reported study was funded by RFBR according to the research project N18-29-03102.

Author information

Authors and Affiliations

  1. Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia

    Maria A. Poltavtseva & Maxim O. Kalinin

Authors
  1. Maria A. Poltavtseva
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  2. Maxim O. Kalinin
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Corresponding author

Correspondence to Maria A. Poltavtseva .

Editor information

Editors and Affiliations

  1. SPIIRAS, St. Petersburg, Russia

    Igor Kotenko

  2. University of Craiova, Craiova, Romania

    Costin Badica

  3. SPIIRAS, St. Petersburg, Russia

    Vasily Desnitsky

  4. LAAS - CNRS, Toulouse Cedex 4, France

    Didier El Baz

  5. University of Novi Sad, Novi Sad, Serbia

    Mirjana Ivanovic

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Poltavtseva, M.A., Kalinin, M.O. (2020). Conceptual Data Modeling Using Aggregates to Ensure Large-Scale Distributed Data Management Systems Security. In: Kotenko, I., Badica, C., Desnitsky, V., El Baz, D., Ivanovic, M. (eds) Intelligent Distributed Computing XIII. IDC 2019. Studies in Computational Intelligence, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-030-32258-8_5

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