# Synchronization of Acoustic Signals for Steganographic Transmission
## 2 Related Work
In [29], a data rate of almost 300 kbit/s was achieved. The method of using the cosine transform to hide data is described in [32]. The data rate of 150 bit/s was achieved, as well as resistance to lossy compression and analogue to digital conversion. An innovative approach to the topic of hiding information in acoustic signals has been proposed in [33; 34]. The authors propose to transform the acoustic signal into an image using the wavelet transform (A2 IWT, Audio to Image Wavelet Transform). Then, embedding the information in the signal is done using one of the known steganography methods for digital images. The features of steganographic algorithms based on signal to image transformation depend on the properties of the image steganography algorithms used in a given case. The paper [35] proposes a mechanism of steganographic data embedding in acoustic signals using the Hermit transform. The presented method is characterized by high perceptual transparency, but the authors do not specify the data rate achieved. The method is resistant to signal noise and filtering. An algorithm based on the statistical properties of the signal was presented in [36]. In [37], the probability density function for the speech signal was proposed. Assuming that the speech signal at the receiver input is the sum of the steganographic signal and the noise signal, in [36] the dependencies on the random variable of this signal were determined. The process of embedding additional information in a single signal frame is done by appropriately scaling the amplitude. The data rate depends on the nature of the original signal and ranges from 172 bit/s for music signals to 40 bit/s for speech signals. The papers [38; 39; 40] present the results confirming the use of the echo signal to create covert channels. These methods confirm effective data extraction in the presence of many signal distorting factors, such as adding noise, changing the sampling frequency, filtering, lossy compression, and transmission over a VoIP link. In [41; 42; 43], methods using the spread spectrum were presented. Algorithms in the field are relatively easy to implement and show good resistance to a wide variety of signal transformations. They meet the requirements for perceptual transparency and provide a hidden data rate of several dozen bits per second. There is, therefore, a relatively small number of articles and technical descriptions of audio systems used to create hidden communication channels. There is a clear gap in this area of knowledge. This is due in part to the realization that the power of the secret channel access key lies not in the number of key combinations but its stealth, i.e., the method of embedding and extracting the steganographic sequence. This is because the space of possible secret channel access key combinations is limited by strongly correlating with the values of the cover signal. The article [44] presents a mathematical description and explanation of this vulnerability. The works on steganographic algorithms presented in this section do not exhaust this extensive issue. It is enough to bear in mind that in electronic publication databases, after entering the keyword audio steganography, only for the years 2018-2019 we get 92 results in the IEEE database, 121 results in the Web of Science database, and as many as 299 results in the Scopus database. On the other hand, the Google Scholar search engine finds 4270 items.