Open AccessCorrected runs distribution test for pseudorandom number generators
Author(s) -
Fan Limin,
Chen Hua,
Chen Meihui,
Gao Si
Publication year - 2016
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2015.3097
Subject(s) - randomness , randomness tests , pseudorandom number generator , test (biology) , nist , mathematics , golomb coding , statistical hypothesis testing , statistics , algorithm , distribution (mathematics) , random number generation , pseudorandomness , computer science , artificial intelligence , paleontology , image compression , mathematical analysis , natural language processing , image (mathematics) , biology , image processing
Runs distribution test is an important statistical test based on Golomb's randomness postulates. It is an important randomness test included in some famous evaluation standards and statistical test suites such as Application Notes and Interpretation of the Scheme (AIS20), the Federal Information Processing Standards (FIPS140), CryptX, and so on. However, when it is applied on some well‐known good Deterministic Random Bit Generators (DRBGs), the test results show apparent bias from randomness. This shows that there exist some inaccuracies in the runs distribution test. The problem is solved and the runs distribution test through two ways is corrected. First, the degree of freedom of statistical value V is adjusted. Secondly, the expected number of different lengths runs is modified. The experiment results show that the corrected runs distribution test is more accurate under two‐level evaluation approach proposed by National Institute of Standards and Technology (NIST) Special Publication (SP) 800–22.