2017
DOI: 10.1109/tifs.2017.2656473
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Randomness Evaluation With the Discrete Fourier Transform Test Based on Exact Analysis of the Reference Distribution

Abstract: In this paper, we study the problems in the discrete Fourier transform (DFT) test included in NIST SP 800-22 released by the National Institute of Standards and Technology (NIST), which is a collection of tests for evaluating both physical and pseudorandom number generators for cryptographic applications. The most crucial problem in the DFT test is that its reference distribution of the test statistic is not derived mathematically but rather numerically estimated; the DFT test for randomness is based on a pseu… Show more

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Cited by 19 publications
(10 citation statements)
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“…It is worth noticing that not all NIST randomness tests are suitable for short keys. For example, the FFT test seems to be unreliable [99,158]. Even flaws in the NIST entropy estimators have been debated [159,160], leaving the entropy estimation an open issue [61].…”
Section: Table 3 Crkg Optimization Parametersmentioning
confidence: 99%
“…It is worth noticing that not all NIST randomness tests are suitable for short keys. For example, the FFT test seems to be unreliable [99,158]. Even flaws in the NIST entropy estimators have been debated [159,160], leaving the entropy estimation an open issue [61].…”
Section: Table 3 Crkg Optimization Parametersmentioning
confidence: 99%
“…DFT test is a powerful evaluation for randomness of pseudo random sequences [8]. This evaluation claims that if a binary sequence is ideally random, the real and imaginary parts of its DFT function are random, independent and both following zero-mean normal distribution.…”
Section: Ffh/ds Reception Under Mtimentioning
confidence: 99%
“…SP800-22 consists of 15 types of randomness tests. Some of the tests were pointed out that are problematic, and improvements have been proposed [6], [7], [8], [9], [10], [11], [12], [13].…”
Section: Introductionmentioning
confidence: 99%