Chaotic-type features for speech steganalysis

Abstract

We investigate the use of chaotic-type features for recorded speech steganalysis. Considering that data hiding within a speech signal distorts the chaotic properties of the original speech signal, we design a steganalyzer that uses Lyapunov exponents and a fraction of false neighbors as chaotic features to detect the existence of a stegosignal. We also discuss the applicability of the proposed method to general audio.