On the interpretation of results from the NIST statistical test
suite

J 2015

On the interpretation of results from the NIST statistical test suite

SÝS, Marek; Zdeněk ŘÍHA; Václav MATYÁŠ; Kinga MÁRTON; Alin SUCIU et al.

Základní údaje

Originální název

On the interpretation of results from the NIST statistical test suite

Autoři

SÝS, Marek; Zdeněk ŘÍHA; Václav MATYÁŠ ; Kinga MÁRTON a Alin SUCIU

Vydání

Romanian Journal of Information Science and Technology, Publishing House of the Romanian Academy, 2015, 1453-8245

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Rumunsko

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 0.269

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14330/15:00081363

Organizační jednotka

Fakulta informatiky

UT WoS

000369852700002

Klíčová slova anglicky

Hypothesis testing; NIST STS; Statistical randomness testing

Změněno: 15. 8. 2019 13:04, prof. RNDr. Václav Matyáš, M.Sc., Ph.D.

Anotace

V originále

NIST Statistical Test Suite is an important testing suite for randomness analysis often used for formal certifications or approvals. Documentation of the NIST STS gives some guidance on how to interpret results of the NIST STS but interpretation is not clear enough or it uses just approximated values. Moreover NIST considers data to be random if all tests are passed yet even truly random data shows a high probability (80%) of failing at least one NIST STS test. If data fail some tests the NIST STS recommends the analysis of different samples. We analysed 819200 sequences (100 GB of data) produced by a physical source of randomness (quantum random number generator) in order to interpret results computed without analysing any additional samples. The results indicate that data can be still considered random for the significance level a = 0.01 if they fail less than 7 NIST STS tests, 7 tests of uniformity of p-values (100 sequences) or 10 tests of proportion of passing sequences. We have also defined a more accurate interval of acceptable proportions computed with a new constant (2.6 instead of 3) for which 1000 sequences can be considered random if they fail less than 7 tests of proportion.

Návaznosti

EE2.3.30.0037, projekt VaV

Název: Zaměstnáním nejlepších mladých vědců k rozvoji mezinárodní spolupráce

GBP202/12/G061, projekt VaV

Název: Centrum excelence - Institut teoretické informatiky (CE-ITI) (Akronym: CE-ITI)

Investor: Grantová agentura ČR, Centrum excelence - Institut teoretické informatiky

Citovat

SÝS, Marek; Zdeněk ŘÍHA; Václav MATYÁŠ; Kinga MÁRTON a Alin SUCIU. On the interpretation of results from the NIST statistical test suite. Romanian Journal of Information Science and Technology. Publishing House of the Romanian Academy, 2015, roč. 18, č. 1, s. 18-32. ISSN 1453-8245.

@article{1322353,
   author = {Sýs, Marek and Říha, Zdeněk and Matyáš, Václav and Márton, Kinga and Suciu, Alin},
   article_number = {1},
   keywords = {Hypothesis testing; NIST STS; Statistical randomness testing},
   language = {eng},
   issn = {1453-8245},
   journal = {Romanian Journal of Information Science and Technology},
   title = {On the interpretation of results from the NIST statistical test suite},
   volume = {18},
   year = {2015}
}

TY  - JOUR
ID  - 1322353
AU  - Sýs, Marek - Říha, Zdeněk - Matyáš, Václav - Márton, Kinga - Suciu, Alin
PY  - 2015
TI  - On the interpretation of results from the NIST statistical test suite
JF  - Romanian Journal of Information Science and Technology
VL  - 18
IS  - 1
SP  - 18-32
EP  - 18-32
PB  - Publishing House of the Romanian Academy
SN  - 14538245
KW  - Hypothesis testing
KW  - NIST STS
KW  - Statistical randomness testing
N2  - NIST Statistical Test Suite is an important testing suite for randomness analysis often used for formal certifications or approvals. Documentation of the NIST STS gives some guidance on how to interpret results of the NIST STS but interpretation is not clear enough or it uses just approximated values. Moreover NIST considers data to be random if all tests are passed yet even truly random data shows a high probability (80%) of failing at least one NIST STS test. If data fail some tests the NIST STS recommends the analysis of different samples. We analysed 819200 sequences (100 GB of data) produced by a physical source of randomness (quantum random number generator) in order to interpret results computed without analysing any additional samples. The results indicate that data can be still considered random for the significance level a = 0.01 if they fail less than 7 NIST STS tests, 7 tests of uniformity of p-values (100 sequences) or 10 tests of proportion of passing sequences. We have also defined a more accurate interval of acceptable proportions computed with a new constant (2.6 instead of 3) for which 1000 sequences can be considered random if they fail less than 7 tests of proportion.
ER  -

SÝS, Marek; Zdeněk ŘÍHA; Václav MATYÁŠ; Kinga MÁRTON a Alin SUCIU. On the interpretation of results from the NIST statistical test suite. \textit{Romanian Journal of Information Science and Technology}. Publishing House of the Romanian Academy, 2015, roč.~18, č.~1, s.~18-32. ISSN~1453-8245.

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