Abstract

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.

Highlights

  • Audio steganography is the process of hiding secret data inside an audio file

  • The Adaptive Multi-level Phase Coding (AMPC) was compared in terms of visual error distribution and SegSNR spikes to capture the effect of the fair payload distribution against sequential embedding

  • It is noticed that existing phase coding methods suffer from low capacity and high retrieval error rates in Least Significant Bit (LSB)-based methods

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Summary

Introduction

Audio steganography is the process of hiding secret data inside an audio file. Audio steganography methods exploited the Human Auditory System (HAS) to convey secret messages. More advanced statistical steganalysis approaches have been introduced recently [1], such as the methods in [2]–[4]. The main challenge in audio steganography is that three main requirements (embedding capacity, transparency, and robustness) must be fulfilled simultaneously [5], [6]. The embedding capacity often referred to as embedding rate, is defined as the maximum message size per 1-time unit.

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