Study on upper limit of sample size for a two-level test in NIST SP800-22

Haramoto, Hiroshi

doi:10.1007/s13160-020-00434-y

Cited by 2 publications

(2 citation statements)

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“…As one of the second-level tests, the uniformity of p-values obtained by the first-level test was tested using the goodness-of-fit test. However, it is known that the exact distribution of p-values differs from the uniform distribution depending on the first-level test [3][4][5]. For the χ 2 test adopted as one of the second-level tests in the test suite NIST SP80022, the effect of this difference on the test results was analyzed, and upper limits of sample size (number of tested sequences) were proposed by F. Pareschi et.…”

Section: Introductionmentioning

confidence: 99%

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Second-level randomness test based on the Kolmogorov-Smirnov test

Yamaguchi¹,

Saito²

2021

Preprint

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We analyzed the effect of the deviation of the exact distribution of the p-values from the uniform distribution on the Kolmogorov-Smirnov (K-S) test that was implemented as the second-level randomness test. We derived an inequality that provides an upper bound on the expected value of the K-S test statistic when the distribution of the null hypothesis differs from the exact distribution. Furthermore, we proposed a second-level test based on the two-sample K-S test with an ideal empirical distribution as a candidate for improvement.

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Section: Introductionmentioning

confidence: 99%

“…For the χ 2 test adopted as one of the second-level tests in the test suite NIST SP80022, the effect of this difference on the test results was analyzed, and upper limits of sample size (number of tested sequences) were proposed by F. Pareschi et. al [3], by H. Haramoto [4], and [5]. Pareschi et.…”

Section: Introductionmentioning

confidence: 99%