A Technique to Test Non-Binary Random Number Generator | Zendy

Anna Epishkina | Zendy

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A Technique to Test Non-Binary Random Number Generator

Author(s) -

Anna Epishkina

Publication year - 2018

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2018.11.039

Subject(s) - computer science , random number generation , pseudorandom number generator , random sequence , binary number , random seed , generator (circuit theory) , convolution random number generator , pseudorandom binary sequence , task (project management) , random function , sequence (biology) , algorithm , theoretical computer science , random variable , arithmetic , statistics , mathematics , mathematical analysis , power (physics) , physics , distribution (mathematics) , management , quantum mechanics , biology , economics , genetics

Nowadays random numbers are used almost everywhere, e.g. in statistical tasks, gambling, information security, artificial intelligence. Quality of output numbers determine the successful task solving. However, a lot of information security tools implementations have not got reliable sources of really random numbers and as a result fail. In order to increase a random number generator rate non-binary random number generators are created. Nevertheless all known mechanisms to test output sequence can be applied only to binary numbers. The author propose a technique to obtain properties of non-binary random sequences based on von Neumann whitening and common known statistical tests.

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