In previous papers we have addressed the problem of testing Random Number Generators (RNGs) through statistical tests, with particular emphasis on the approach we called second-level testing. We have shown that this approach is capable of achieving much higher accuracy in exposing non-random generators, but may suffer from reliability issues due to approximations introduced in the test. Here we consider the NIST Frequency Test and present a mathematical expression of the error introduced by approximating the effective discrete distribution function with its continuous limit distribution. The matching against experimental data is almost perfect.
On the Approximation Errors in the Frequency Test Included in the NIST SP800-22 Statistical Test Suite
PARESCHI, Fabio;SETTI, Gianluca
2008
Abstract
In previous papers we have addressed the problem of testing Random Number Generators (RNGs) through statistical tests, with particular emphasis on the approach we called second-level testing. We have shown that this approach is capable of achieving much higher accuracy in exposing non-random generators, but may suffer from reliability issues due to approximations introduced in the test. Here we consider the NIST Frequency Test and present a mathematical expression of the error introduced by approximating the effective discrete distribution function with its continuous limit distribution. The matching against experimental data is almost perfect.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
