Improving random number generators by chaotic iterations. Application in data hiding

TL;DR

This paper introduces a new chaotic iteration-based pseudo-random number generator that combines XOR-shift methods, passing all DieHARD tests and exhibiting chaos, making it suitable for cryptography and data hiding applications.

Contribution

The paper presents a novel PRNG combining chaotic iterations with XOR-shift, improving statistical properties and demonstrating robustness in data hiding.

Findings

Generator passes all DieHARD tests.

Exhibits chaotic behavior per Devaney.

Effective in data hiding with robustness against attacks.

Abstract

In this paper, a new pseudo-random number generator (PRNG) based on chaotic iterations is proposed. This method also combines the digits of two XORshifts PRNGs. The statistical properties of this new generator are improved: the generated sequences can pass all the DieHARD statistical test suite. In addition, this generator behaves chaotically, as defined by Devaney. This makes our generator suitable for cryptographic applications. An illustration in the field of data hiding is presented and the robustness of the obtained data hiding algorithm against attacks is evaluated.