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Using information theory approach to randomness testing. (English) Zbl 1062.62004
Summary: We address the problem of detecting deviations of binary sequences from randomness,which is very important for random number (RNG) and pseudorandom number generators (PRNG). Namely, we consider a null hypothesis $$H_0$$ that a given bit sequence is generated by a Bernoulli source with equal probabilities of 0 and 1 and the alternative hypothesis $$H_1$$ that the sequence is generated by a stationary and ergodic source which differs from the source under $$H_0$$. We show that data compression methods can be used as a basis for such testing and describe two new tests for randomness, which are based on ideas of universal coding. Known statistical tests and suggested ones are applied for testing PRNGs. These experiments show that the power of the new tests is greater than that of many known algorithms.

##### MSC:
 62B10 Statistical aspects of information-theoretic topics 62G10 Nonparametric hypothesis testing 65C10 Random number generation in numerical analysis 94A29 Source coding
##### Software:
NIST Statistical Test Suite
Full Text:
##### References:
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