Highly transparent steganography model of speech signals using Efficient Wavelet Masking

► We design a steganography model of speech-in-speech signals. ► The model, Efficient Wavelet Masking, is based on the masking property of the HAS. ► The core is the efficient sorting of the wavelet coefficients of the secret message. ► EWM and other methods such as LSB, FM, SS, SSA, have been analyzed. ► Statistical transparency is better in EWM than in LSB, FM, SS and SSA. Steganography is the process of hiding information on a host signal. Transparency is referred to the ability to avoid suspicion about the existence of a secret message. The most popular mechanisms for hiding data in audio signals are the Least Significant Bit (LSB) substitution, Frequency Masking (FM), Spread Spectrum (SS), and Shift Spectrum Algorithm (SSA). In this paper, we adapt the Frequency Masking concept using an efficient sorting of the wavelet coefficients of the secret messages and use an indirect LSB substitution for hiding speech signals into speech signals. The experimental results show that the proposed model, the Efficient Wavelet Masking (EWM) scheme, has a hiding capacity significantly higher than the Spread and Shift Spectrum Algorithms and additionally a statistical transparency higher than all of the above mentioned mechanisms. Moreover, the transparency is not dependent of the host signal chosen because the wavelet sorting guarantees the adaptation of the secret message to the host signal.