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Application of algorithmic information theory to calibrate tests of random number generators. / Ryabko, Boris.

2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 61-65 (2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Ryabko, B 2021, Application of algorithmic information theory to calibrate tests of random number generators. in 2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021. 2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021, Institute of Electrical and Electronics Engineers Inc., pp. 61-65, 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021, Moscow, Russian Federation, 25.10.2021. https://doi.org/10.1109/REDUNDANCY52534.2021.9606440

APA

Ryabko, B. (2021). Application of algorithmic information theory to calibrate tests of random number generators. In 2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021 (pp. 61-65). (2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/REDUNDANCY52534.2021.9606440

Vancouver

Ryabko B. Application of algorithmic information theory to calibrate tests of random number generators. In 2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 61-65. (2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021). doi: 10.1109/REDUNDANCY52534.2021.9606440

Author

Ryabko, Boris. / Application of algorithmic information theory to calibrate tests of random number generators. 2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 61-65 (2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021).

BibTeX

@inproceedings{5d8177a90f7c4f359acd7ed4022af841,
title = "Application of algorithmic information theory to calibrate tests of random number generators",
abstract = "Currently, statistical tests for random number generators (RNGs) are widely used in practice, and some of them are even included in information security standards. But despite the popularity of RNGs, consistent tests are known only for stationary ergodic deviations of randomness (a test is consistent if it detects any deviations from a given class when the sample size goes to infinity). However, the model of a stationary ergodic source is too narrow for some RNGs, in particular, for generators based on physical effects. In this article, we propose computable consistent tests for some classes of deviations more general than stationary ergodic and describe some general properties of statistical tests. The proposed approach and the resulting test are based on the ideas and methods of information theory.",
keywords = "algorithmic information theory, information theory, Kolmogorov complexity, physical random number generators, random number generator, randomness testing, statistical test",
author = "Boris Ryabko",
note = "Funding Information: Research was supported by Russian Foundation for Basic Research (grant no. 18-29-03005). Publisher Copyright: {\textcopyright} 2021 IEEE.; 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021 ; Conference date: 25-10-2021 Through 29-10-2021",
year = "2021",
doi = "10.1109/REDUNDANCY52534.2021.9606440",
language = "English",
isbn = "9781665433082",
series = "2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "61--65",
booktitle = "2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021",
address = "United States",

}

RIS

TY - GEN

T1 - Application of algorithmic information theory to calibrate tests of random number generators

AU - Ryabko, Boris

N1 - Funding Information: Research was supported by Russian Foundation for Basic Research (grant no. 18-29-03005). Publisher Copyright: © 2021 IEEE.

PY - 2021

Y1 - 2021

N2 - Currently, statistical tests for random number generators (RNGs) are widely used in practice, and some of them are even included in information security standards. But despite the popularity of RNGs, consistent tests are known only for stationary ergodic deviations of randomness (a test is consistent if it detects any deviations from a given class when the sample size goes to infinity). However, the model of a stationary ergodic source is too narrow for some RNGs, in particular, for generators based on physical effects. In this article, we propose computable consistent tests for some classes of deviations more general than stationary ergodic and describe some general properties of statistical tests. The proposed approach and the resulting test are based on the ideas and methods of information theory.

AB - Currently, statistical tests for random number generators (RNGs) are widely used in practice, and some of them are even included in information security standards. But despite the popularity of RNGs, consistent tests are known only for stationary ergodic deviations of randomness (a test is consistent if it detects any deviations from a given class when the sample size goes to infinity). However, the model of a stationary ergodic source is too narrow for some RNGs, in particular, for generators based on physical effects. In this article, we propose computable consistent tests for some classes of deviations more general than stationary ergodic and describe some general properties of statistical tests. The proposed approach and the resulting test are based on the ideas and methods of information theory.

KW - algorithmic information theory

KW - information theory

KW - Kolmogorov complexity

KW - physical random number generators

KW - random number generator

KW - randomness testing

KW - statistical test

UR - http://www.scopus.com/inward/record.url?scp=85123292341&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/1d1fb93a-7259-3a55-872d-97bb6c91e6fc/

U2 - 10.1109/REDUNDANCY52534.2021.9606440

DO - 10.1109/REDUNDANCY52534.2021.9606440

M3 - Conference contribution

AN - SCOPUS:85123292341

SN - 9781665433082

T3 - 2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021

SP - 61

EP - 65

BT - 2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021

Y2 - 25 October 2021 through 29 October 2021

ER -

ID: 35304384