Abstract
Generators of pseudorandom sequences are widely used in practice. Generators of pseudorandom bit sequences occupy a special place among them; they are necessary for solving a number of important tasks, for example, for strong cryptography. The impossibility of predicting the following values of pseudorandom sequences is one of the basic requirements for such generators. Otherwise, these generators cannot be used to protect of information. It is generally accepted that if the stochastic sequence is stationary, then the prediction of such sequence is impossible. Our research shows that there are invariants for specific pseudorandom sequences that can be used to this prediction.
The article is devoted to the method of prediction of pseudorandom bit sequences. The values of the autocorrelation coefficients for some lags are used. Good results are obtained for software-implemented stationary stochastic sequences.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chethan, J., Lakkannavar, M.: Design of low power test pattern generator using low transition LFSR for high fault coverage analysis. Int. J. Inf. Eng. Electron. Bus. (IJIEEB) 5(2), 15–21 (2013). https://doi.org/10.5815/ijieeb.2013.02.03
Ivanov, M.A., Chugunkov, I.V.: Cryptographic methods of information protection in computer systems and networks: a teaching manual. NIUA MIFI, Moscow (in Russian) (2012)
Jhansirani, A., Harikishore, K., Basha, F., et al.: Fault tolerance in bit swapping LFSR using FPGA architecture. Int. J. Eng. Res. Appl. 2(1), 1080–1087 (2012)
Kitsos, O., Sklava, P., Zervas, N., et al.: A reconfigurable linear feedback shift register (LFSR) for the bluetooth system. ICECS (2001). https://doi.org/10.1109/ICECS.2001.957640
Klapper, A., Goresky, M.: 2-Adic shift registers. In: Fast Software Encryption, Cambridge Security Workshop Proceedings, pp. 174–178. Springer (1994)
Maksymovych, V., Shevchuk, M., Mandrona, M.: Research pseudorandom bit sequence generators based on LFSR. J. Autom. Measur. Control 852, 29–34 (2016). (in Ukraine)
Maksymovych, V., Mandrona, M.: Investigation of the statistical characteristics of the modified fibonacci generators. J. Autom. Inf. Sci. (2014). https://doi.org/10.1615/JAutomatInfScien.v46.i12.60
Maksymovych, V., Mandrona, M.: Comparative analysis of pseudorandom bit sequence generators. J. Autom. Inf. Sci. (2017). https://doi.org/10.1615/JAutomatInfScien.v49.i3.90
Maksymovych, V., Mandrona, M., Garasimchuk, O., Kostiv, Yu.: A study of the characteristics of the fibonacci modified additive generator with a delay. J. Autom. Inf. Sci. (2016). https://doi.org/10.1615/JAutomatInfScien.v48.i11.70
Ali, M.A., Ali, E., Habib, M.A., Nadim, M., Kusaka, T., Nogami, Y.: Pseudo random ternary sequence and its autocorrelation property over finite field. Int. J. Comput. Netw. Inf. Secur. (IJCNIS) 9(9), 54–63 (2017). https://doi.org/10.5815/ijcnis.2017.09.07
Milovanovic, E., Stojcev, M., Milovanovic, I., et al.: Concurrent generation of pseudo random numbers with LFSR of fibonacci and galois type. Comput. Inform. 34, 941–958 (2015)
Mondal, A., Pujari, S.: A novel approach of image based steganography using pseudorandom sequence generator function and DCT coefficients. Int. J. Comput. Netw. Inf. Secur. (IJCNIS) 7(3), 42–49 (2015). https://doi.org/10.5815/ijcnis.2015.03.06
Nas, R.J., Van Berkel, C.H.: High throughput, low set-up time, reconfigurable linear feedback shift registers. In: International Conference on Computer Design (2010). https://doi.org/10.1109/iccd.2010.5647572
Ndaw, B.A., Sow, D., Sanghare, M.: Construction of the maximum period linear feedback shift registers (LFSR) (Primitive Polynomials and Linear Recurring Relations). Br. J. Math. Comput. Sci. (2015). https://doi.org/10.9734/BJMCS/2015/19442
NIST SP 800-22. A Statistic Test Suite for Random and Pseudorandom Number Generators for Cryptographic Application. DIALOG: http://csrc.nist.gov/publications/niatpubs/SP800-22rev1a.pdf. Accessed Apr 2000
Nanda, S.K., Tripathy, D.P., Nayak, S.K., Mohapatra, S.: Prediction of rainfall in india using artificial neural network (ANN) models. Int. J. Intell. Syst. Appl. (IJISA) 5(12), 1–22 (2013). https://doi.org/10.5815/ijisa.2013.12.01
Schneier, B.: Applied cryptography, protocols, and algorithms for source code in C. Triumph, Moscow (2002). (in Russia)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Maksymovych, V., Nyemkova, E., Shevchuk, M. (2019). Statistic Properties and Cryptographic Resistance of Pseudorandom Bit Sequence Generators. In: Hu, Z., Petoukhov, S., Dychka, I., He, M. (eds) Advances in Computer Science for Engineering and Education. ICCSEEA 2018. Advances in Intelligent Systems and Computing, vol 754. Springer, Cham. https://doi.org/10.1007/978-3-319-91008-6_44
Download citation
DOI: https://doi.org/10.1007/978-3-319-91008-6_44
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-91007-9
Online ISBN: 978-3-319-91008-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)