Steganalysis of Audio Based on Audio Quality Metrics

Abstract

Classification of audio documents as bearing hidden information or not is a security issue addressed in the context of steganalysis. A cover audio object can be converted into a stego-audio object via steganographic methods. In this study we present a statistical method to detect the presence of hidden messages in audio signals. The basic idea is that, the distribution of various statistical distance measures, calculated on cover audio signals and on stego-audio signals vis-à-vis their denoised versions, are statistically different. The design of audio steganalyzer relies on the choice of these audio quality measures and the construction of a two-class classifier. Experimental results show that the proposed technique can be used to detect the presence of hidden messages in digital audio data.