Randomness enhancement for a Digitalized Modified-Logistic Map based Pseudo Random Number Generator

Abstract

A nonlinear, Digitalized Modified-Logistic Map based Pseudo Random Number Generator (DMLM-PRNG) is proposed for randomness enhancement. We use parameter selection to reduce computation cost and output sequence scrambling to improve the quality or randomness. Statistical test results show that DMLM-PRNG passes all cases in SP800-22, and most of cases in Crush, one of the test suite of TesuU01. When compared to previous chaotic map based PRNGs, in terms of randomness quality, our system is as good as Addabbo's [1] combined system and better than Li's [2] system. Moreover, our system shows better scalability than Addabbo's system.