Abstract
This paper is studies modeling data in big data systems, including polystores and other heterogeneous information processing components. Currently, several works propose to harmonize polystore data models in this domain. This study considers various proposed methods; however, these solutions are not suitable for direct use for solving information security problems. Requirements on modeling the considered objects for solving security tasks and the level-sensitive modeling method based on the general security concept of polystores within a consistent approach are formulated. This study presents an authentic classification of the structure of data models of modern polystores and DBMSs, taking into account the mathematical framework in use. A new methodology of three-level modeling of data and processes in an object for protection is proposed; and the basics of models for all data representation levels are formulated. The results of this study lay the foundation for the integrated representation of data and processes for solving security problems and analyzing the security of big data systems.
REFERENCES
Duggan, J., Elmore, A.J., Stonebraker, M., Balazinska, M., Howe, B., Kepner, J., Madden, S., Maier, D., Mattson, T., and Zdonik, S., The BigDAWG polystore system, ACM SIGMOD Rec., 2015, vol. 44, no. 2, pp. 11–16. https://doi.org/10.1145/2814710.2814713
Özsu, M.T. and Valduriez, P., Distributed and parallel database design, Principles of Distributed Database Systems, Cham: Springer, 2020, vol. 674, pp. 33–89. https://doi.org/10.1007/978-3-030-26253-2_2
Holubová, I., Svoboda, M., and Lu, J., Unified management of multi-model data, Conceptual Modeling, Oliveira, J., Ed., Lecture Notes in Computer Science, vol. 439, Cham: Springer, 2019, pp. 439–447. https://doi.org/10.1007/978-3-030-33223-5_36
Krishnapriya, V.M., Libin, S., and Gibin, G., A study for integrating SQL and NoSQL databases, Int. Conf. on Intellectual Property Rights, 2021, pp. 79–85. https://www.ijsr.net/conf/ICIPR2021/ICIPR2021_16.pdf. Cited September 19, 2023.
Lu, J. and Holubová, I., Multi-model databases, ACM Comput. Surv., 2019, vol. 52, no. 3, pp. 1–38. https://doi.org/10.1145/3323214
Ong, K.W., Papakonstantinou, Y., and Vernoux, R., The SQL++ query language: Configurable, unifying and semi-structured, 2014. https://doi.org/10.48550/arXiv.1405.3631
ISO/IEC 9075-14:2011: Information technology–Database languages–SQL–Part 14: XML-related specifications (SQL/XML), 2011.
ISO/IEC TR 19075-6:2017 Information technology–Database languages–SQL–Part 6: SQL support for JavaScript object notation (JSON), 2017.
Schultz, P., Spivak, D.I., Vasilakopoulou, C., and Wisnesky, R., Algebraic databases, 2016. https://doi.org/10.48550/arXiv.1602.03501
Koupil, P., Svoboda, M., and Holubova, I., MM-cat: A tool for modeling and transformation of multi-model data using category theory, 2021 ACM/IEEE Int. Conf. on Model Driven Engineering Languages and Systems Companion (MODELS-C), Fukuoka, Japan, 2021, IEEE, 2021, pp. 635–639. https://doi.org/10.1109/models-c53483.2021.00098
Poltavtseva, M.A. and Kalinin, M.O., Conceptual data modeling using aggregates to ensure large-scale distributed data management systems security, Intelligent Distributed Computing XIII, Kotenko, I., Badica, C., Desnitsky, V., El Baz, D., and Ivanovic, M., Eds., Studies in Computational Intelligence, vol. 868, Cham: Springer, 2019, pp. 41–47. https://doi.org/10.1007/978-3-030-32258-8_5
Shinavier, J., Wisnesky, R., and Meyers, J.G., Algebraic property graphs, 2019. https://doi.org/10.48550/arXiv.1909.0488
Uotila, V. and Lu, J., A formal category theoretical framework for multi-model data transformations, Heterogeneous Data Management, Polystores, and Analytics for Healthcare, Rezig, E.K. , Eds., Lecture Notes in Computer Science, vol. 12921, Cham: Springer, 2021, pp. 14–28. https://doi.org/10.1007/978-3-030-93663-1_2
Uotila, V., Lu, J., Gawlick, D., Liu, Zh.H., Das, S., and Pogossiants, G., Multi-model query processing meets category theory and functional programming, CEUR Workshop Proc., 2021, vol. 2929, pp. 48–49.
Uotila, V., Lu, J., Gawlick, D., Liu, Zh.H., Das, S., and Pogossiants, G., MultiCategory: Multi-model query processing meets category theory and functional programming, Proc. VLDB Endowment, vol. 14, no. 12, pp. 2663–2666. https://doi.org/10.14778/3476311.3476314
Koupil, P., Crha, D., and Holubová, I., A universal approach for simplified redundancy-aware cross-model querying, Proc. 26th Int. Conf. on Extending Database Technology, EDBT 2023, Ioannina, Greece, 2023, OpenProceedings.org, 2023, pp. 831–834.
Gobert, M., Meurice, L., and Cleve, A., Conceptual modeling of hybrid polystores, Conceptual Modeling, Ghose, A., Horkoff, J., Silva Souza, V.E., Parsons, J., and Evermann, J., Eds., Lecture Notes in Computer Science, vol. 13011, Cham: Springer, 2021, pp. 113–122. https://doi.org/10.1007/978-3-030-89022-3_10
Roy-Hubara, N. and Sturm, A., Design methods for the new database era: A systematic literature review, Software Syst. Model., 2020, vol. 19, no. 2, pp. 297–312. https://doi.org/10.1007/s10270-019-00739-8
Gobert, M., Meurice, L., and Cleve, A., HyDRa: A framework for modeling, manipulating and evolving hybrid polystores, 2022 IEEE Int. Conf. on Software Analysis, Evolution and Reengineering (SANER), Honolulu, Hawaii, 2022, IEEE, 2022, pp. 652–656. https://doi.org/10.1109/saner53432.2022.00082
Poltavtseva, M.A., Zegzhda, D.P., and Kalinin, M.O., Multilevel security concept of big data management systems, Vopr. Kiberbezopasnosti, 2023, no. 5.
Meier, A. and Kaufmann, M., NoSQL databases, SQL & NoSQL Databases, Wiesbaden: Springer Vieweg, 2019, pp. 201–218. https://doi.org/10.1007/978-3-658-24549-8_7
Funding
The study was supported by the grant of Russian Science Foundation no. 23-11-20003, https://rscf.ru/project/23-11-20003/; grant of St. Petersburg Science Foundation (agreement no. 23-11-20003 on the regional grant).
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Translated by S. Kuznetsov
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Poltavtseva, M.A. Data Modeling in Big Data Systems Including Polystore and Heterogeneous Information Processing Components. Aut. Control Comp. Sci. 57, 1096–1102 (2023). https://doi.org/10.3103/S0146411623080266
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DOI: https://doi.org/10.3103/S0146411623080266