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Data protection in heterogeneous big data systems

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Abstract

Modern Big Data systems are notable for their scale and, often, their distributed organization. A feature of a number of Big Data systems is the use of heterogeneous data processing tools. These are different DBMS and streaming processing tools with different data granularity. The input information may be repeatedly fragmented and re-grouped as it moves between storage locations. In this case, the problems of data integrity, access control and auditing cannot be solved by traditional methods. This paper considers the security of heterogeneous Big Data systems based on distributed ledger technologies and verifiable zero-knowledge operations.

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Funding

The work was performed as part of the State assignment for basic research (topic code 0784-2020-0026).

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Author notes

  1. E. B. Aleksandrova, V. S. Shmatov and P. D. Zegzhda contributed equally to this work.

Authors and Affiliations

  1. Institute of Cyber Security and Information Protection, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia

    M. A. Poltavtseva, E. B. Aleksandrova, V. S. Shmatov & P. D. Zegzhda

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  1. M. A. Poltavtseva
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  2. E. B. Aleksandrova
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  3. V. S. Shmatov
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  4. P. D. Zegzhda
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Correspondence to M. A. Poltavtseva.

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Poltavtseva, M.A., Aleksandrova, E.B., Shmatov, V.S. et al. Data protection in heterogeneous big data systems. J Comput Virol Hack Tech 19, 451–458 (2023). https://doi.org/10.1007/s11416-023-00472-3

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