Audio steganography allows and inspires many researchers to design methods for secure communication. Based on the evaluation on the existing methods, it was found that most methods focused on one or two requirements while disregarding others, causing imbalanced performance. Moreover, most methods lack adaptivity and dynamic allocation. Therefore, in this research, a method called Adaptive Multi-level Phase Coding (AMPC) was proposed to optimize the above issues. The reverse logic of the main tradeoffs was used to empirically design several embedding levels that that simultaneously attained good performance for all aspects as much as possible. Then, an adaptive component was added by selecting the embedding level that provided the best performance for each embedding process. Moreover, the error spreading factor was introduced to achieve a fair payload distribution. The performance balance objective requires a new formulation that will enable the accurate selection of the degree of modification, multiple-bit embedding per modification, and reduced retrieval errors. As a result, the interval centering quantization (ICQ) was formulated and implemented in the proposed method. The experimental results show that AMPC successfully fulfilled the research objectives. Also, AMPC surpassed other phase coding methods in all aspects while time-domain methods achieved the highest transparency and capacity with the lowest robustness. Moreover, experiments show that the implementation of adaptive multi-level concept is able to improve the existing method's performance significantly. In summary, AMPC was able to achieve a stable embedding rate of 33 Kbps at 35 dB of SNR, which is higher than the recorded embedding rate of other phase coding methods.

Audio steganography refers to hiding a secret message inside a cover audio file. The existing methods follow almost a sequential embedding which leads to poor utilization of the cover. The proposed method aims to achieve the maximum feasible capacity of the audio file without lowering the quality. The proposed method is based on seven levels of thresholds and six LSB layers, while the embedding is carried out progressively. The method allocates the message bits over the cover signal horizontally to ensure fair payload distribution over the signal. Hence, the selected samples might be visited multiple times till the message is totally embedded. The experimental results show that the method is able to reach a hiding capacity of 40% of the file size or 266.6 kbps while maintaining an SNR and PSNR values of 40 and 58 dB respectively. It is concluded that the proposed progressive method is highly adaptive to the message size and capable of providing high-quality stego even when big payloads are used. The comparative study shows that the progressive method provides the best message distribution based on the nature of the cover.

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