The rapid spread in digital data usage in many real life applications have urged new and effective ways to ensure their security. Efficient secrecy can be achieved, at least in part, by implementing steganograhy techniques. Novel and versatile audio steganographic methods have been proposed. The goal of steganographic systems is to obtain secure and robust way to conceal high rate of secret data. We focus in this paper on digital audio steganography, which has emerged as a prominent source of data hiding across novel telecommunication technologies such as covered voice-over-IP, audio conferencing, etc. The multitude of steganographic criteria has led to a great diversity in these system design techniques. In this paper, we review current digital audio steganographic techniques and we evaluate their performance based on robustness, security and hiding capacity indicators. Another contribution of this paper is the provision of a robustness-based classification of steganographic models depending on their occurrence in the embedding process. A survey of major trends of audio steganography applications is also discussed in this paper.

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In this paper, we present a unified algorithm for phase and magnitude speech spectra data hiding. The phase and the magnitude speech spectra are concurrently investigated to increase the capacity and the security of the embedded information. The proposed algorithm in this paper is based on finding secure spectral embedding areas in wideband magnitude speech spectrum. Our approach exploits these areas to hide data in both speech components (i.e., phase and magnitude). The embedding locations and hiding capacity are defined according to a controlled acceptable distortion in the magnitude spectrum. The latter is expressed as a set of parameters controlled by the sender. Consequently, the hiding capacity and the locations of concealed data change for each data communication instance to further prevent malicious intrusions. Objective results show that the presented algorithm in this paper secures hidden data and achieves interesting tradeoffs between the hiding capacity and the speech quality. Copyright © 2013 John Wiley & Sons, Ltd.