A Generalized Chaos-Based Stream Generator

Abstract

In this paper, a general key stream generator based on discrete chaotic maps is presented. The new design of generator is to divide the attractor of a chaotic system into equal subregions, which are associated with 0 or 1 dynamically. The analysis and experimental results demonstrate that it is an efficient way to generate key streams with desired long cycle length. Moreover, the generated key streams have good statistical properties such as the uniform distribution, δ-like auto-correlation function, and near-zero crosscorrelation function, etc.