Associative Protection of Numerical Information in Text Documents Using the Parallel Framework Library on the .NET Platform
( Pp. 121-129)

More about authors
Gibadullin Ruslan F. Candidate of Engineering; Associate Professor at the Department of Computer Systems,
Kazan National Research Technical University named after A.N. Tupolev – KAI
Kazan, Republic of Tatarstan, Russian Federation Vershinin Igor S. Candidate of Engineering, Associate Professor; Head of the Department of Computer Systems; Kazan National Research Technical University named after A.N. Tupolev – KAI; Kazan, Republic of Tatarstan, Russian
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The paper discusses the development and analysis of an application designed to protect numeric data in text files using an associative data protection mechanism. The application, based on the .NET platform and using the Parallel Framework library, was tested in detail to evaluate the effectiveness of multithreaded data processing and the use of regular expressions to extract numeric information from text. The results showed that the application of parallel processing can significantly increase performance, achieving twice the speedup on a multi-core hardware platform. At the same time, the paper highlights and analyzes some of the challenges and limitations associated with parallel processing, including user interface locking, the need for thread safety, and the peculiarities of working with regular expressions in multithreaded mode. Possible directions for further improvement of the application are discussed. The conducted research is of practical value for the development of parallel data processing methods in the context of information protection.
How to Cite:
Gibadullin R.F., Vershinin I.S. Associative Protection of Numerical Information in Text Documents Using the Parallel Framework Library on the .NET Platform. Computational Nanotechnology. 2023. Vol. 10. No. 3. Pp. 121–129. (In Rus.) DOI: 10.33693/2313-223X-2023-10-3-121-129. EDN: STEVDR
Reference list:
Raikhlin V.A., Vershinin I.S., Gibadullin R.F., Pystogov S.V. Reliable recognition of masked binary matrices. Connection to information security in map systems. Lobachevski Journal of Mathematics. 2013. Vol. 34. Pp. 319–325.
Raikhlin V.A., Gibadullin R.F., Vershinin I.S., Pystogov S.V. Reliable recognition of masked cartographic scenes during transmission over the network: Materials of the International Siberian Conference on Control and Communications (SIBCON). 2016. Pp. 1–5.
Anwar F., Rachmawanto E.H., Atika Sari C., Setiadi D.R.I.M. StegoCrypt Scheme using LSB-AES Base64: Materials of the International Conference on Information and Communications Technology (ICOIACT). 2019. Pp. 85–90.
Garcia A.M., Griebler D., Fernandes L.G.L., Schepke C.Introducing a stream processing framework for assessing parallel programming interfaces: Materials of the 29th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP). 2021. Pp. 84–88.
Gibadullin R.F., Gashigullin D.A., Vershinin I.S. Development of the StegoStream decorator for associative protection of byte stream. Modeling, optimization and information technologies. 2023. Vol. 11. No. 2. (In Rus.) URL:
Braude E. Incremental UML for Agile Development: Embedding UML Class Models in Source Code. 2017 IEEE/ACM 3rd International Workshop on Rapid Continuous Software Engineering (RCoSE). 2017. Pp. 27-31.
Sharmila L., Sakthi U., Geethanjali A., Sagadevan S. Regular expression based pattern matching for gene expression data to identify the abnormality gnome: Materials of the Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM). 2017. Pp. 301–305.
Parallel Framework, parallel processing, associative security mechanism, .NET platform, Parallel Framework, regular expressions, thread security, numeric data, text files, data protection.

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