Hiding data in audio files: A smoothing-based approach to improve the quality of the stego audio

Abstract

In this digital era, transmitting data through a computer network has become common. Moreover, some applications have also been developed to do it. Nevertheless, users may not be aware of the security aspect of this data transmission, which can lead to disclosing this private message. In a case when a sensitive message is the object to transmit, a security mechanism should be applied. Data hiding is one of the methods introduced to work for this issue. In this algorithm, the message is embedded into the cover, such as an audio file, before being transmitted; on the other side, the recipient extracts it. However, the size of the message and the quality of the resulted stego data are still challenging. In this paper, we focus on these two problems by considering some factors: embedding space, embedding process, reducing, and smoothing steps. Firstly, the audio signal is discretized to obtain audio samples. Next, these samples are interpolated to provide spaces for hiding the secret. Considering that the quality of the generated stego audio is likely to drop, reducing and smoothing steps are designed. The experimental results show that this approach can improve the quality of the stego based on the specified payload capacity. That is, there is an increase in PSNR value of at least 10 dB, depending on the payload size and the methods.

Reversible data hiding with segmented secrets and smoothed samples in various audio genres

“…On the other hand, [29] takes various numbers of the bit to hide, while [28] sets it as a fixed number. Next, this feature is adopted in [30] and [31], where respectively Newton's Divided Difference Interpolation (NDDI) and linear interpolation methods are implemented.…”

“…It can also be an advantage, considering that a user may have a unique preference. In the next research, the noise in the stego audio is decreased by applying multiple-smoothing [31]. Furthermore, an additional step is also implemented, called a reducing step.…”

“…Initially, the NMI and NDDI interpolation algorithms, which are implemented in [28,29,30], respectively, have inspired us to use them. Nevertheless, the linear method employed in [31] potentially delivers an equivalent result. Therefore, we take this simpler algorithm in our design.…”

“…Moreover, [32,33], which do not take the interpolation at all, may have a relatively lower capacity. Each sample's payload size in [32,33] is static, which is different from that of [30,31]. So, the payload's dynamic (non-static) size and the smoothing step have also been our focus in this research.…”

“…For example, Jung and Yoo [28,29] propose the use of an interpolation algorithm for the embedding space. Next, Ahmad and Fiqar [30] explore the quality of the stego audio, which is then further refined in [31]. Previously, Andra et al [32] focused on the protection of medical data, also by using audio, while Bobeica et al [33] extended the concept of PEE.…”