A new discrete Fourier transform randomness test

Chen, Meihui; Chen, Hua; Fan, Li; Zhu, Shaofeng; Xi, Wei; Feng, Dan

doi:10.1007/s11432-018-9489-x

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…When the runs distribution test is applied on some well-known good deterministic random bit generators (DRBGs), the test results show apparent bias from randomness [19]. A new DFT test method for the long sequence is proposed, and this DFT test reconstructs the statistics to follow the chi-square distribution [20].…”

Section: Introductionmentioning

confidence: 99%

Fast Software Implementation of Serial Test and Approximate Entropy Test of Binary Sequence

Yang

Zhan

Kang

et al. 2021

Security and Communication Networks

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In many cryptographic applications, random numbers and pseudorandom numbers are required. Many cryptographic protocols require using random or pseudorandom numbers at various points, e.g., for auxiliary data in digital signatures or challenges in authentication protocols. In NIST SP800-22, the focus is on the need for randomness for encryption purposes and describes how to apply a set of statistical randomness tests. These tests can be used to evaluate the data generated by cryptographic algorithms. This paper will study the fast software implementation of the serial test and the approximate entropy test and propose two types of fast implementations of these tests. The first method is to follow the basic steps of these tests and replace bit operations with byte operations. Through this method, compared with the implementation of Fast NIST STS, the efficiency of the serial test and approximate entropy test is increased by 2.164 and 2.100 times, respectively. The second method is based on the first method, combining the statistical characteristics of subsequences of different lengths and further combining the two detections with different detection parameters. In this way, compared to the individual implementation of these tests, the efficiency has been significantly improved. Compared with the implementation of Fast NIST STS, the efficiency of this paper is increased by 4.078 times.

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Section: Introductionmentioning

confidence: 99%