A comparative study and analysis of some pseudorandom number generator algorithms. Issue 6 (4th October 2018)

• Record Type: Journal Article
• Authors: Sinha, Shobhit; Islam, SK Hafizul; Obaidat, Mohammad S.
• Is Part Of: Security and privacy. Volume 1:Issue 6(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-10-04
• Subjects: LCG -- MIXMAX -- NIST test suit -- PRNG -- WELL -- WichMann‐Hill; Computer security -- Periodicals; Data protection -- Periodicals; Cyberterrorism -- Periodicals; 005.8
• DOI: 10.1002/spy2.46
• Languages: English
• ISSNs: 2475-6725

Abstract

Abstract : In this article, we have investigated the statistical nature of popular pseudorandom number generators (PRNGs) present in the literature and have analyzed their performance against the battery of tests prescribed in NIST SP800‐22rev1a. Different tests performed in this article provide an insight into the PRNGs and have revealed if they are statistically random or not, which is the first criteria in being cryptographically secure. In our study, we have considered the following PRNGs: (a) Linear Congruential Generator, (b) WichMann‐Hill Algorithm, (c) Well Equidistributed Long Period Generator and (d) MIXMAX.