An AAC steganography scheme for adaptive embedding with distortion minimization model
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An AAC steganography scheme for adaptive embedding with distortion minimization model Zhenyu Zhang1,2 · Xiaowei Yi1,2 · Xianfeng Zhao1,2 Received: 12 November 2019 / Revised: 16 June 2020 / Accepted: 13 July 2020 / © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Nowadays, most prevailing approaches to advanced audio coding (AAC) steganography are content non-adaptive which have low embedding capacity and poor security. In this paper, we construct a new distortion by integrating the uniform embedding distortion with the masking threshold, and propose an adaptive steganographic scheme for AAC audio by modifying quantized modified discrete cosine transform (QMDCT) coefficients. To hold the statistical distribution of QMDCT coefficients we introduce uniform embedding idea. Then the psychoacoustic model is used to avoid the declining of hearing quality. Finally, we minimize the overall embedding distortion by utilizing syndrome-trellis codes (STCs) technique and the defined distortion function. Comprehensive experimental results show that the proposed scheme achieves better performance than related works. The detection error of 128-kbps-AAC dataset is higher than 24.78% when the embedding payload reaches 3.70 kbps, which is significantly lower than the state-of-the-art AAC steganographic methods. Keywords AAC · Adaptive steganography · QMDCT coefficients · Psychoacoustic model · Uniform embedding This work was supported by NSFC under 61902391, 61972390, U1736214, 61802393 and 61872356, National Key Technology R&D Program under 2019QY0701, 2019QY2202 and 2019QY(Y)0207, and IIE CAS Climbing Program. Xianfeng Zhao
[email protected] Zhenyu Zhang [email protected] Xiaowei Yi [email protected] 1
State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China
2
School of Cyber Security, University of Chinese Academy of Sciences, Beijing, 100093, China
Multimedia Tools and Applications
1 Introduction MPEG-2/4 Advanced Audio Coding (AAC) is a new generation of encoding standard for compressing audio files, which is the widely used in video or audio public platforms such as YouTube and iTunes. Therefore, it is a suitable carrier for hiding secret messages. Audio steganography is a modern science of covert communication that slightly changes the original audio files in order to hide secret messages without drawing perceptual suspicions [4, 14]. Many audio steganographic algorithms have been proposed for AAC files [22, 24–26, 28, 30, 31]. However, they generally have low embedding capacity and serious perceptual distortion. In addition, with the development of steganalysis methods for AAC audio [16, 18], the security of the existing AAC steganographic algorithms is decreased significantly. Therefore a security and high capacity AAC steganography algorithm is inevitable tendency in modern audio steganography. With the development of steganographic techniques, AAC audio steganography has become a research hotspot
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