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

Результат исследования: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаярецензирование

Аннотация

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.

Язык оригиналаанглийский
Название основной публикации2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021
ИздательInstitute of Electrical and Electronics Engineers Inc.
Страницы61-65
Число страниц5
ISBN (электронное издание)9781665433082
DOI
СостояниеОпубликовано - 2021
Событие17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021 - Moscow, Российская Федерация
Продолжительность: 25 окт 202129 окт 2021

Серия публикаций

Название2021 17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021

Конференция

Конференция17th International Symposium Problems of Redundancy in Information and Control Systems, REDUNDANCY 2021
СтранаРоссийская Федерация
ГородMoscow
Период25.10.202129.10.2021

Предметные области OECD FOS+WOS

  • 1.01 МАТЕМАТИКА
  • 1.02 КОМПЬЮТЕРНЫЕ И ИНФОРМАЦИОННЫЕ НАУКИ

Fingerprint

Подробные сведения о темах исследования «Application of algorithmic information theory to calibrate tests of random number generators». Вместе они формируют уникальный семантический отпечаток (fingerprint).

Цитировать