An Adaptive High Capacity Model for Secure Audio Communication Based on Fractal Coding and Uniform Coefficient Modulation

Abstract

Securing confidential information over an unsecured communication channel and environment has become an essential aspect. This paper proposes high-capacity audio steganography model based on fractal coding and uniform coefficient modulation, which will be called as HASFC, that simultaneously adjusts the data hiding requirements by increasing the hiding capacity while maintaining the transparency and robustness. HASFC model is based on cover-secret mapping, uniform coefficients modulation and hybrid chaotic map techniques in the transform domain using lifting wavelet. The efficiency of the proposed model is evaluated using a set of experiments, and the audio files are selected from the GTZAN dataset. The empirical findings show improvement in hiding capacity by 30% in comparison with similar techniques in the wavelet domain. Moreover, the transparency is preserved with 50 dB SNR and 4.8 SDG, on average. Furthermore, the proposed model is robust to some signal processing attacks and steganalysis using statistical methods such as the fourth first moment and histogram error ratio. The results signify that the proposed model has notably enhanced the performance of the audio steganography comparing with the related works.