Chaotic cellular neural network-based true random number generator

Abstract

This paper presents implementation of a chaotic cellular neural network (CNN)-based true random number generator on a field programmable gate array (FPGA) board. In this implementation, discrete time model of the chaotic CNN is used as the entropy source. Random number series are generated for three scenarios. Obtained number series are tested by using NIST 800.22 statistical test suite. Also, the scale index technique is carried out for these three scenarios to determine the degree of non-periodicity for key stream. Copyright (c) 2017 John Wiley & Sons, Ltd.