High-SNR steganography for digital audio signal in the wavelet domain
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High-SNR steganography for digital audio signal in the wavelet domain Shuo-Tsung Chen 1 & Tsai-Wei Huang 2 & Chao-Tung Yang 3 Received: 23 October 2019 / Revised: 18 September 2020 / Accepted: 24 September 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
Imperceptible, robust, and embedding capacity are three main requirements for the steganography of digital audio signal. To enhance them, this study presents a novel steganography for digital audio signal in the wavelet domain. Since the performance of imperceptible and robust are usually in term of signal-to-noise ratio (SNR) and bit-error-rate (BER), we propose a quantization-based optimization model to maximize SNR and reduce BER in embedding secret message. In the proposed model, quantization technique with unknow coefficients of discrete wavelet transform (DWT) is rewritten as the first constraint. The adjustment of scaling DWT coefficients is considered as the second constraint. At the same time, signal-to-noise ratio (SNR) is converted into a performance index. In solving this model, we use matrix operations and Lagrange multiplier to obtain optimal DWT coefficients and scaling factors. Moreover, the invariant feature of the scaling factors against amplitude scaling attack is proved. In extraction, secret message can be detected without original audio signal. Experimental results show that the proposed steganography has high SNR and strong robustness against many malicious attacks when comparing to some exiting methods. Keywords Digital audio signal . Signal-to-noise ratio . Bit-error-rate . Discrete wavelet transform . Scaling factors . Optimization
1 Introduction Due to the rapid development of the network and communication, the transmission of digital information has become a part of daily life, and thus copyright protection technology such as * Chao-Tung Yang [email protected] Shuo-Tsung Chen [email protected] Tsai-Wei Huang [email protected] Extended author information available on the last page of the article
Multimedia Tools and Applications
steganography or watermarking has become a research topic [1, 4–19, 23, 24, 26–31]. For basic performance requirements of International Federation of the Phonographic Industry (IFPI), a steganography for digital audio signal should make secret message imperceptible in the embedded audio, offer more than 20 dB signal-to-noise ratio (SNR), and provide at least 20 bps (bits per-second) embedding capacity. Moreover, the steganography should be able to protect the secret message against common attacks such as re-sampling, mp3 compression, filtering, amplitude scaling, time-scaling, and so on. Transform domain is an useful platform in developing a steganography for digital audio signal. In [5], authors proposed an entropy-based audio watermarking scheme in the wavelet domain. They defined energy entropy and derive many useful properties of this energy entropy with respect to audio watermarking but the SNR is very poor and the attack resistance is weak in addition to the ampli
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