Cryptographically Secured Pseudo-Random Number Generators: Analysis and Testing with NIST Statistical Test Suite
There are several areas of knowledge in which (pseudo-)random numbers are necessary, for example, in statistical–mathematical simulation or in cryptography and system security, among others. Depending on the area of application, it will be necessary that the sequences used meet certain requirements....
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/23/4812 |
| _version_ | 1827592262911000576 |
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| author | Elena Almaraz Luengo Javier Román Villaizán |
| author_facet | Elena Almaraz Luengo Javier Román Villaizán |
| author_sort | Elena Almaraz Luengo |
| collection | DOAJ |
| description | There are several areas of knowledge in which (pseudo-)random numbers are necessary, for example, in statistical–mathematical simulation or in cryptography and system security, among others. Depending on the area of application, it will be necessary that the sequences used meet certain requirements. In general, randomness and uniformity conditions are required in the generated sequences, which are checked with statistical tests, and conditions on sequence unpredictability if the application is in security. In the present work, a literature review on cryptographically secure pseudo-random number generators (CSPRNGs) is carried out, they are implemented, and a critical analysis of their statistical quality and computational efficiency is performed. For this purpose, different programming languages will be used, and the sequences obtained will be checked by means of the NIST Statistical Test Suite (NIST STS). In addition, a user’s guide will be provided to allow the selection of one generator over another according to its statistical properties and computational implementation characteristics. |
| first_indexed | 2024-03-09T01:47:12Z |
| format | Article |
| id | doaj.art-a886ee37df544fb79705d7bce24d9849 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T01:47:12Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-a886ee37df544fb79705d7bce24d98492023-12-08T15:21:50ZengMDPI AGMathematics2227-73902023-11-011123481210.3390/math11234812Cryptographically Secured Pseudo-Random Number Generators: Analysis and Testing with NIST Statistical Test SuiteElena Almaraz Luengo0Javier Román Villaizán1Department of Statistics and Operational Research, Faculty of Mathematical Science, Complutense University of Madrid, 28040 Madrid, SpainFaculty of Mathematical Science, Complutense University of Madrid, 28040 Madrid, SpainThere are several areas of knowledge in which (pseudo-)random numbers are necessary, for example, in statistical–mathematical simulation or in cryptography and system security, among others. Depending on the area of application, it will be necessary that the sequences used meet certain requirements. In general, randomness and uniformity conditions are required in the generated sequences, which are checked with statistical tests, and conditions on sequence unpredictability if the application is in security. In the present work, a literature review on cryptographically secure pseudo-random number generators (CSPRNGs) is carried out, they are implemented, and a critical analysis of their statistical quality and computational efficiency is performed. For this purpose, different programming languages will be used, and the sequences obtained will be checked by means of the NIST Statistical Test Suite (NIST STS). In addition, a user’s guide will be provided to allow the selection of one generator over another according to its statistical properties and computational implementation characteristics.https://www.mdpi.com/2227-7390/11/23/4812cryptographically secured pseudo-random number generatorshypothesis testingNIST STStest batterytest suite |
| spellingShingle | Elena Almaraz Luengo Javier Román Villaizán Cryptographically Secured Pseudo-Random Number Generators: Analysis and Testing with NIST Statistical Test Suite Mathematics cryptographically secured pseudo-random number generators hypothesis testing NIST STS test battery test suite |
| title | Cryptographically Secured Pseudo-Random Number Generators: Analysis and Testing with NIST Statistical Test Suite |
| title_full | Cryptographically Secured Pseudo-Random Number Generators: Analysis and Testing with NIST Statistical Test Suite |
| title_fullStr | Cryptographically Secured Pseudo-Random Number Generators: Analysis and Testing with NIST Statistical Test Suite |
| title_full_unstemmed | Cryptographically Secured Pseudo-Random Number Generators: Analysis and Testing with NIST Statistical Test Suite |
| title_short | Cryptographically Secured Pseudo-Random Number Generators: Analysis and Testing with NIST Statistical Test Suite |
| title_sort | cryptographically secured pseudo random number generators analysis and testing with nist statistical test suite |
| topic | cryptographically secured pseudo-random number generators hypothesis testing NIST STS test battery test suite |
| url | https://www.mdpi.com/2227-7390/11/23/4812 |
| work_keys_str_mv | AT elenaalmarazluengo cryptographicallysecuredpseudorandomnumbergeneratorsanalysisandtestingwithniststatisticaltestsuite AT javierromanvillaizan cryptographicallysecuredpseudorandomnumbergeneratorsanalysisandtestingwithniststatisticaltestsuite |