Visible to the public Statistical Randomness Tests of Long Sequences by Dynamic Partitioning

TitleStatistical Randomness Tests of Long Sequences by Dynamic Partitioning
Publication TypeConference Paper
Year of Publication2020
AuthorsAKCENGİZ, Ziya, Aslan, Melis, Karabayır, Özgür, Doğanaksoy, Ali, Uğuz, Muhiddin, Sulak, Fatih
Conference Name2020 International Conference on Information Security and Cryptology (ISCTURKEY)
Date PublishedDec. 2020
PublisherIEEE
ISBN Number978-1-6654-1863-8
KeywordsCollaboration, composability, cryptography, cryptology, Generators, Human Behavior, human factors, Indexes, Information security, Mathematics, Metrics, NIST, NIST SP 800-22, pubcrawl, random number, Random variables, randomness, resilience, resilient, Scalability, test suites
AbstractRandom numbers have a wide usage in the area of cryptography. In practice, pseudo random number generators are used in place of true random number generators, as regeneration of them may be required. Therefore because of generation methods of pseudo random number sequences, statistical randomness tests have a vital importance. In this paper, a randomness test suite is specified for long binary sequences. In literature, there are many randomness tests and test suites. However, in most of them, to apply randomness test, long sequences are partitioned into a certain fixed length and the collection of short sequences obtained is evaluated instead. In this paper, instead of partitioning a long sequence into fixed length subsequences, a concept of dynamic partitioning is introduced in accordance with the random variable in consideration. Then statistical methods are applied. The suggested suite, containing four statistical tests: Collision Tests, Weight Test, Linear Complexity Test and Index Coincidence Test, all of them work with the idea of dynamic partitioning. Besides the adaptation of this approach to randomness tests, the index coincidence test is another contribution of this work. The distribution function and the application of all tests are given in the paper.
URLhttps://ieeexplore.ieee.org/document/9308005
DOI10.1109/ISCTURKEY51113.2020.9308005
Citation Keyakcengiz_statistical_2020