Summary
2020
Session Number:C01
Session:
Number:C01-2
The time-adaptive statistical testing for random number generators
Boris Ryabko, Viacheslav Zhuravlev,
pp.344-347
Publication Date:2020/10/18
Online ISSN:2188-5079
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Summary:
The problem of constructing effective statistical tests for random number generators (RNG) is considered. Currently, there are hundreds of RNG statistical tests that are often combined into so-called batteries, each containing from a dozen to more than one hundred tests. When a battery test is used, it is applied to a sequence generated by the RNG, and the calculation time is determined by the length of the sequence and the number of tests. Generally speaking, the longer the sequence, the smaller deviations from randomness can be found by a specific test. So, when a battery is applied, on the one hand, the ``better'' tests are in the battery, the more chances to reject a ``bad'' RNG. On the other hand, the larger the battery, the less time can be spent on each test and, therefore, the shorter the test sequence. In turn, this reduces the ability to find small deviations from randomness. To reduce this trade-off, we propose an adaptive way to use batteries (and other sets) of tests that can be used in such a way as to increase the testing power.