Comparative analysis of digital noise generated by additive Fibonacci generators

Author:

Isakov O. V.ORCID, ,Voitusik S. S.ORCID,

Abstract

Noise generators and pseudorandom number generators (PRNGs) are widely used in the field of information technology, including cybersecurity, for modeling, authorization key generation, and technical protection of information. It has been found that the characteristics of digital noise directly depend on the chosen PRNG algorithm. To determine the quality of the generated noise, special tests are performed, which are primarily applied to the sequence generated by the PRNG. The results of digital noise generated by an PRNG based on four different algorithms of additive Fibonacci generators (AFG) are investigated. The choice of generators of the same type allowed us to analyze the effect of different modifications on the final result of the generated sequences to determine their advantages and disadvantages. Digital signal processing techniques such as frequency, autocorrelation and visual analysis, signal-to-noise ratio, and statistical tests of the NIST package were used to test the noise and generated sequences. Functions for interpreting the obtained data were developed using the MATLAB (DSP System Toolbox) application package and the C programming language for automating NIST tests. It has been found that for effective testing, specific stages and their sequence should be determined: determination of the PRNG period, statistical tests of the NIST package, calculation of the autocorrelation function, and other methods of digital signal processing. It was found that modification of one AFG by using a carry bit (MAFG2) does not improve the results of the generated sequence, unlike the PIKE algorithm, which consists of three AFGs. The MAFG algorithm showed better results during the period testing and at the same time passed NIST tests, unlike the unmodified version. The dependence between the order of the generated sequences and the results of their autocorrelation function was revealed. It is proposed that, in addition to general statistical tests, applied tests should be carried out when choosing or developing a new generator, its effectiveness should be checked under the conditions required by existing standards and requirements. The compliance of the generated digital noise with the requirements for devices for technical protection of information, namely the protection of speech information, has been established.

Publisher

Lviv Polytechnic National University

Subject

General Medicine

Reference14 articles.

1. Brent, R. P. (1992). Uniform random number generators for supercomputers.

2. Ferguson, N., Schneier, B., & Kohno, T. (2010). Cryptography Engineering: Design Principles and Practical Applications.

3. SP 800-22 Rev. 1a. A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications. (2010). SP 800-22 Rev. 1a. A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications.

4. Mohamed, M. A., Awang, M. I. (2017). An empirical analysis of six pseudo-random number generators. Far East Journal of Electronics and Communications, 17, 6, 1373-1388. http://dx.doi.org/10.17654/EC017061373

5. Kamalika, B., Sukanta, D. (2022). A search for good pseudo-random number generators: Survey and empirical studies. Computer Science Review, 45, 100471. https://doi.org/10.1016/j.cosrev.2022.100471

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