Development of a Software Package for the Implementation of the Algorithm Berlecamp – Messy on Simple Shift Registers with Linear Feedback for Students of the Discipline “Cryptography”
( Pp. 97-104)

More about authors
Sharipov Rifat R. Cand. Sci. (Eng.); associate professor, Department of Information Security Systems (ISS)
Kazan National Research Technical University named after A.N. Tupolev – KAI
Kazan, Republic of Tatarstan, Russian Federation Kassirova Aleksandra A. Department of Information Security Systems (ISS); Kazan National Research Technical University named after A.N. Tupolev – KAI; Kazan, Republic of Tatarstan, Russian Federation
Abstract:
In this paper, the Berlecamp – Messy algorithm, its features and the relevance of using this algorithm for various tasks are discussed. A simple linear feedback shift register (LFSR) has been chosen and the general circuit of the register is presented. The Berlecamp – Messy algorithm has been implemented in the C# proramming language using the WTF platform, the graphical shell of the developed complex has been shown, the block diagram of the algorithm has been given and the program code has been presented. Demonstration of the complex operation on the example of bit stream of the RSLOS generator and comparison with the calculated values is carried out. The results of the work can be used for creation of more perfect data protection systems and training of future specialists, the developed pro-software complex and presented algorithms can be used in the educational process within the discipline “Cryptography” for students in the direction of “Information Security”.
How to Cite:
Sharipov R.R., Kassirova A.A. Development of a Software Package for the Implementation of the Algorithm Berlecamp – Messy on Simple Shift Registers with Linear Feedback for Students of the Discipline “Cryptography”. Computational Nanotechnology. 2025. Vol. 12. No. 1. Pp. 97–104. (In Rus.). DOI: 10.33693/2313-223X-2025-12-1-97-104. EDN: MRQUHZ
Reference list:
Gavrishev A.A., Zhuk A.P. Application of the Berlekamp – Massey algorithm for quantitative analysis of secure communication systems. Applied Informatics. 2019. No. 14 (4). Pp. 118–134. (In Rus.)
Ratseev S.M., Lavrinenko A.D., Stepanova E.A. On the Berlekamp – Massey algorithm and its application in decoding algorithms. Bulletin of Samara University. Natural Science Series. 2021. No. 27 (1). Pp. 44–61. (In Rus.)
Voronchikhin I.A., Baturin M.A., Atmanskikh M.B. Efficient hardware implementations of cryptographic shift registers. In: mathematical and information modeling: Proceedings of the All-Russian Conference of Young Scientists. 2021. Vol. 19. Pp. 266–274.
Makarov S.P. Software implementation of LFSR. In: Applied electrodynamics, photonics, and living systems – 2024. Abstracts of the XI International Youth Scientific and Technical Conference (Kazan, April 11–12, 2024). Kazan: IP Sagiev A.R., 2024. Pp. 870–871.
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Kassirova A.A., Sharipov R.R. Research on vulnerabilities of the CHAP authentication protocol. In: Information technologies in science, industry, and education. Proceedings of the All-Russian Scientific and Technical Conference (Izhevsk, May 23–24, 2024). Izhevsk: Kalashnikov Izhevsk State Technical University, 2024. Pp. 381–384.
Gibadullin R.F., Lekomtsev D.V., Perukhin M.Yu. Analysis of industrial network parameters using neural network processing. Artificial Intelligence and Decision Making. 2020. No. 1. Pp. 80–87. (In Rus.)
Makarov S.P., Sharipov R.R. Software implementation of the KASUMI block encryption algorithm. In: Information technologies in science, industry, and education. Proceedings of the All-Russian Scientific and Technical Conference (Izhevsk, May 23–24, 2024). Izhevsk: Kalashnikov Izhevsk State Technical University, 2024. Pp. 385–388.
Makarov S.P. Software implementation of the RC4 algorithm. In: Applied electrodynamics, photonics, and living systems – 2024. Abstracts of the XI International Youth Scientific and Technical Conference (Kazan, April 11–12, 2024). Kazan: IP Sagiev A.R., 2024. Pp. 868–869.
Keywords:
human pose estimation, neurological rehabilitation, deep learning, machine vision, automated motion diagnostics.


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