Abstract
The article presents hardware modified additive Fibonacci generators, which use modular addition, with the base of the prime number. Generators differ from the classical presence in their composition of the logic circuit, which is the base of arithmetic addition of an additional component, thus enhancing the chaotic nature of the formation of random numbers. The analysis of statistical characteristics of these generators for large values of arguments is carried out. The implementation of the proposed generator structures allows, in comparison with known devices significant increasing the repetition period of the generated pseudo-random sequence for the vast majority of initial settings of structural elements of the circuit while providing satisfactory statistical characteristics of the output sequence. This will contribute to the improvement of the characteristics of existing systems that include generators of pseudorandom sequences and to the expansion of their scope of use.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Schneier, B.: Applied Cryptography: Protocols, Algorithms, and Source Code in C, p. 578. Wiley, New Jersey, USA (2007)
Gorbenko I.D., Gorbenko Y.I.: Applied Cryptology: Theory. Practice. Application, p. 754. Fort Publishing House, Kharkiv, Ukraine (2012)
Maksymovych, V., Kostiv, Y., Mandrona, M., Harasymchuk, O.: Generator of pseudorandom bit sequence with increased cryptographic immunity. Metall. Min. Ind. 6, 24–28 (2014)
Maksymovych, V., et al.: Simulation of authentication in information-processing electronic devices based on poisson pulse sequence generators. Electronics 11(13), 2039 (2022)
Karpinski, M., Maksymovych, V., Harasymchuk, O., Sawicki, D., Shabatura, M., Jancarczyk, P.: Development of additive Fibonacci generators with improved characteristics for cybersecurity needs. Appl. Sci. 12(3), 1519 (2022)
Maksymovych, V., Karpinski, M., Harasymchuk, O., Kajstura, K., Shabatura, M., Jancarczyk, D.: A new approach to the development of additive fibonacci generators based on prime numbers. Electronics 10(23), 2912 (2022)
Maksymovych, V.N., Mandrona, M.N.: Comparative analysis of pseudorandom bit sequence generators. J. Autom. Inf. Sci. 49(3), 78–86 (2017)
Shabatura, M.M., Maksymovych, V.M., Harasymchuk, O.I.: Dosimetric detector hardware simulation model based on modified additive fibonacci generator. Adv. Intell. Syst. 938, 162–171 (2019)
Maksymovych, V.N., Mandrona, M.N., Harasymchuk, O.I.: Designing generators of poisson pulse sequences based on the additive fibonacci generators. J. Autom. Inf. Sci. 49(12), 1–12 (2017)
Maksymovych, V.N., Harasymchuk, O.I., Kostiv, Y.M., Mandrona, M.N.: Investigating the statistical characteristics of poisson pulse sequences generators constructed in different ways. J. Autom. Inf. Sci. 49(10), 11–19 (2017)
Maksymovych, V., Kostiv, Y., Garasimchuk, O., Mandrona, M.: A study of the characteristics of the fibonacci modified additive generator with a delay. J. Autom. Inf. Sci. 48, 76–82 (2016)
Maksymovych, V., Harasymchuk, O., Opirskyy, I.: The designing and research of generators of poisson pulse sequences on base of fibonacci modified additive generator. In: Zhengbing, H., Petoukhov, S., Dychka, I., He, M. (eds.) ICCSEEA 2018. AISC, vol. 754, pp. 43–53. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-91008-6_5
Maksymovych, V., Shevchuk, R., Shabatura, M., Sawicki, P., Harasymchuk, O., Zajac, T.: Combined pseudo-random sequence generator for cybersecurity. Sensors 22(24), 9700 (2022)
Milovanovic, E.I., Milovanovic, I.Z., Stojcev, M.K., Stamenkovic, Z., Nikolic, T.R.: Concurrent generation of pseudo random numbers with lfsr of fibonacci and galois type. Comput. Inform. 34(4), 941–958 (2015)
Chen, J., Su, J., Kochan, O., Levkiv, M.: Metrological software test for simulating the method of determining the thermocouple error in situ during operation. Measure. Sci. Rev. 18(2), 52–58 (2018)
Fang, M.T., Chen, Z.J., Przystupa, K., Li, T., Majka, M., Kochan, O.: Examination of abnormal behavior detection based on improved YOLOv3. Electronics 10(2), 197 (2021)
Away, Y., Noor, R.S.: FPGA-based design system for a two-segment fibonacci lfsr random number generator. Int. J. Electric. Comput. Eng. 7(4), 1882–1891 (2017)
Dichtl, M., Golić, J.D.: High-speed true random number generation with logic gates only. In: Paillier, P., Verbauwhede, I. (eds.) CHES 2007. LNCS, vol. 4727, pp. 45–62. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-74735-2_4
Barker, E.B., Kelsey, J.M.: Recommendation for random bit generator (RBG) constructions. Gaithersburg, USA (2016)
Baldanzi, L., et al.: Cryptographically secure pseudo-random number generator IP-core based on SHA2 algorithm. Sensors 20(7), 1869 (2020)
Kietzmann, P., Schmidt, T.C., Wählisch, M.: A guideline on pseudorandom number generation (PRNG) in the IoT. CSUR 54(6), 1–38 (2021)
Souaki G., Halim K.: Random number generation based on MCU sources for IoT application. ATSIP, Morroco, pp. 1–6 (2017)
Fujdiak, R., Mlynek, P., Misurec, J., Masek, P. Design of low-power random number generator using signal quantization error in smart grid. TSP, pp. 7–10 (2016)
Park, S., Kim, K., Nam, C.: Dynamical pseudo-random number generator using reinforcement learning. Appl. Sci. 12(7), 3377 (2022)
Hu, Z., Dychka, I., Sulema, Y., Radchenko, Y.: Graphical data steganographic protection method based on bits correspondence scheme. IJISA 9(8), 34–40 (2017)
Hu, Z., Dychka, I., Onai, M., Zhykin, Y.: Blind payment protocol for payment channel networks. IJCNIS 11(6), 22–28 (2019). https://doi.org/10.5815/ijcnis.2019.06.03
Hu Z., Gnatyuk S., Okhrimenko T., Tynymbayev S., Iavich M.: High-speed and secure PRNG for cryptographic applications. IJCNIS 12(3), 1–10 (2020). https://doi.org/10.5815/ijcnis.2020.03.01
Knut, D.: The Art of Computer Programming, p. 386. Fundamental algorithms. Massachusets, USA (1998)
Maksymovych, V., Stakhiv, R., Stakhiv, M.: Modified structure of two-level digital frequency synthesizer for dosimetry. Measur. Equip. Metrol. 80(1), 17–20 (2019)
Hurley Smith D., Hernandez Castro J.: Great expectations: a critique of current approaches to random number generation testing & certification. In: Proceedings 4th International Conference, SSR Darmstadt, Germany, pp. 143–163 (2018)
NIST SP 800-22: A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications (2010). https://nvlpubs.nist.gov/nistpubs/Legacy/SP/nistspecialpublication800-22r1a.pdf
Acknowledgment
The studies carried out in within the project Research & Development of Ukraine «Generator» №0122U000954.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Maksymovych, V., Przystupa, K., Harasymchuk, O., Shabatura, M., Stakhiv, R., Kuts, V. (2023). Hardware Modified Additive Fibonacci Generators Using Prime Numbers. In: Hu, Z., Dychka, I., He, M. (eds) Advances in Computer Science for Engineering and Education VI. ICCSEEA 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 181. Springer, Cham. https://doi.org/10.1007/978-3-031-36118-0_44
Download citation
DOI: https://doi.org/10.1007/978-3-031-36118-0_44
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-36117-3
Online ISBN: 978-3-031-36118-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)