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

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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.

Original languageEnglish
Title of host publication2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages61-65
Number of pages5
ISBN (Electronic)9781665433082
DOIs
Publication statusPublished - 2021
Event17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021 - Moscow, Russian Federation
Duration: 25 Oct 202129 Oct 2021

Publication series

Name2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021

Conference

Conference17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021
CountryRussian Federation
CityMoscow
Period25.10.202129.10.2021

Keywords

  • algorithmic information theory
  • information theory
  • Kolmogorov complexity
  • physical random number generators
  • random number generator
  • randomness testing
  • statistical test

OECD FOS+WOS

  • 1.01 MATHEMATICS
  • 1.02 COMPUTER AND INFORMATION SCIENCES

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