TestU01: A C library for empirical testing of random number generators
ACM Transactions on Mathematical Software (TOMS)
Chaotic keystream generator using coupled NDFs with parameter perturbing
CANS'06 Proceedings of the 5th international conference on Cryptology and Network Security
IEEE Transactions on Signal Processing
Research on the quantifications of chaotic random number generators
International Journal of Sensor Networks
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In this brief, a nonlinear digitalized modified logistic map-based pseudorandom number generator (DMLM-PRNG) is proposed for randomness enhancement. Two techniques, i.e., constant parameter selection and output sequence scrambling, are employed to reduce the computation cost without sacrificing the complexity of the output sequence. Statistical test results show that with only one multiplication, DMLM-PRNG passes all cases in SP800-22. Moreover, it passes most of the cases in Crush, one of the test suites of TesuU01. When compared with solutions based on digitized pseudochaotic maps previously proposed in the literature, in terms of randomness quality, our system is as good as a Rényi-map-based PRNG and better than a logistic-map-based PRNG. Moreover, compared with solutions based on a Rényi-map-based PRNG, DMLM-PRNG is better scalable to high digital resolutions with reasonable area overhead.