Department of Computer Science and Automatics, University of Bielsko-Biala, 43-309 Bielsko-Biala, Poland.
Department of Telecommunication and Radio-Electronic Systems, National Aviation University, 03058 Kyiv, Ukraine.
Sensors (Basel). 2022 Aug 4;22(15):5832. doi: 10.3390/s22155832.
The developed method of steganographic hiding of text information in an audio signal based on the wavelet transform acquires a deep meaning in the conditions of the use by an attacker of deliberate unauthorized manipulations with a steganocoded audio signal to distort the text information embedded in it. Thus, increasing the robustness of the stego-system by compressing the steganocoded audio signal subject to the preservation of the integrity of text information, taking into account the features of the psychophysiological model of sound perception, is the main objective of this scientific research. The task of this scientific research is effectively solved using a multilevel discrete wavelet transform using adaptive block normalization of text information with subsequent recursive embedding in the low-frequency component of the audio signal and further scalar product of the obtained coefficients with the Daubechies wavelet filters. The results of the obtained experimental studies confirm the hypothesis, namely that it is proposed to use recursive embedding in the low-frequency component (approximating wavelet coefficients) followed by their scalar product with wavelet filters at each level of the wavelet decomposition, which will increase the average power of hidden data. It should be noted that upon analyzing the existing method, which is based on embedding text information in the high-frequency component (detailed wavelet coefficients), at the last level of the wavelet decomposition, we obtained the limit CR = 6, and in the developed, CR = 20, with full integrity of the text information in both cases. Therefore, the resistance of the stego-system is increased by 3.3 times to deliberate or passive compression of the audio signal in order to distort the embedded text information.
基于小波变换的文本信息隐写方法的发展，在攻击者故意对隐编码音频信号进行未经授权的操作以扭曲其中嵌入的文本信息的情况下，获得了更深层次的意义。因此，通过在考虑声音感知心理生理模型的特征的情况下压缩隐编码音频信号，以保持嵌入的文本信息的完整性，提高隐写系统的鲁棒性是本科学研究的主要目标。本科学研究的任务是使用多级离散小波变换有效地解决，该变换使用自适应块归一化对文本信息进行处理，随后将其递归嵌入到音频信号的低频分量中，并进一步将获得的系数与 Daubechies 小波滤波器进行标量积。所获得的实验研究结果证实了假设，即建议在每个小波分解级别使用递归嵌入低频分量（逼近小波系数），然后用小波滤波器对其进行标量积，这将增加隐藏数据的平均功率。应当指出的是，在分析基于在小波分解的最后一级将文本信息嵌入到高频分量（详细小波系数）的现有方法时，我们得到了限制 CR = 6，而在开发的方法中，CR = 20，在这两种情况下都能完全保持文本信息的完整性。因此，隐写系统的抗干扰能力提高了 3.3 倍，可以故意或被动地压缩音频信号以扭曲嵌入的文本信息。
