Randomness enhancement using digitalized modified logistic map

Shih Liang Chen*, Tingting Hwang, Wen-Wei Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

64 Scopus citations


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 Rnyi-map-based PRNG and better than a logistic-map-based PRNG. Moreover, compared with solutions based on a Rnyi-map-based PRNG, DMLM-PRNG is better scalable to high digital resolutions with reasonable area overhead.

Original languageEnglish
Article number5659895
Pages (from-to)996-1000
Number of pages5
JournalIEEE Transactions on Circuits and Systems I: Regular Papers
Issue number12
StatePublished - 1 Dec 2010


  • Discrete chaos
  • logistic map
  • pseudorandom number generator (PRNG)

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