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New statistical randomness tests: 4-bit template matching tests
Author(s) -
Fatih Sulak
Publication year - 2017
Publication title -
turkish journal of mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.454
H-Index - 27
eISSN - 1303-6149
pISSN - 1300-0098
DOI - 10.3906/mat-1509-19
Subject(s) - nist , randomness , randomness tests , test suite , matching (statistics) , template matching , template , statistical hypothesis testing , algorithm , random number generation , computer science , generator (circuit theory) , mathematics , data mining , theoretical computer science , statistics , artificial intelligence , test case , image (mathematics) , power (physics) , physics , regression analysis , quantum mechanics , natural language processing , programming language
For cryptographic algorithms, secret keys should be generated randomly as the security of the system depends on the key and therefore generation of random sequences is vital. Randomness testing is done by means of statistical randomness tests. In this work, we show that the probabilities for the overlapping template matching test in the NIST test suite are only valid for a specific template and need to be recalculated for the other templates. We calculate the exact distribution for all 4-bit templates and propose new randomness tests, namely template matching tests. The new tests can be applied to any sequence of minimum length 5504 whereas the overlapping template matching test in the NIST test suite can only be applied to sequences of minimum length 10 . Moreover, we apply the proposed tests to biased nonrandom data and observe that the new tests detect the nonrandom behavior of the generator even for a bias of 0.001, whereas the template matching tests in NIST cannot detect that bias.

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