# Direct Spread Spectrum Technology for Data Hiding in Audio +
## 2 Related Works  
Hiding data in audio was investigated in many related papers, e.g., in papers [25; 26; 27; 28; 29], the simplest LSB techniques were studied, which, nevertheless, have some advantages. By encoding the LSB of the container, you can hide a very large amount of data. However, LSBtechniques are also easily detected, and this is their main drawback. Various authors tried to improve LSB. In [26], the authors used augmentation operations to increase resistance to attacks. In [25], the LSB method was applied to the coefficients of the discrete wavelet transform. In [27], an LSB was proposed with an adaptive number of hiding bits for each audio sample (depending on the size of the hidden data, the size of the covering carrier, and the signal-to-noise ratio). In [28], binary data values were hidden in different places to increase security. In [29], the LSB technique was supplemented with data encryption. There are many other works in this area; however, each improvement of the LSB method leads, as a rule, to a decrease in the volume of hidden data [30; 31].  
Other approaches to hiding data in audio use various techniques: in [32], Cochlear Delay Characteristics were used to hide data; in [33], authors investigated bit reduction techniques; in [34; 35; 36], echo signals were used; in [37; 38; 39], data were hidden in the phases of audio signals. All these techniques have their advantages and disadvantages [31]. In particular, the amount of hidden data is significantly less than in LSB methods. However, the security of the hidden data is higher.  
One of the prospective methods is steganography with direct spectrum expansion. These techniques combine high throughput and data security.  
The first works [20; 21; 40] were devoted to the substantiation of the general concepts and structure of the steganosystem using a direct spread spectrum. Images were used to hide the messages. Already in those articles, the authors noted several conflicting requirements [41]. In particular, increasing the size of messages leads to increasing the corruption of containers; small BER values can be achieved only with a large \"energy\" of the embedded message, which significantly distorts the container. In order to eliminate some of these contradictions, the authors suggested using special filtering and correcting codes [41]. These and other ideas were developed in subsequent works. For example, in [42], correction codes were investigated; in [43; 44], a discrete cosine transform (DCT) was implemented together with the direct spreading of the spectrum, etc. Papers [45; 46] are devoted to the study of chaos. In works [47; 48], hiding information in video data was studied, and in [49; 42], audio signals were used for hiding information. Indeed, hiding messages in audio signals is a promising direction [50]; these methods can be used, for example, to protect the property rights of digital audio signals [51].  
Note that in these numerous works, the properties of spreading sequences (chip codes) were almost not explored. The exceptions are our two recent works [23; 24], in which we analyzed various methods of forming spreading sequences, as well as their influence on the characteristics of Spread Spectrum Image Steganography.  
In this work, we continued our research and expanded their field to audio files. First, we looked at different ways to form spreading sequences and explored BER, MSE, and PSNR. Then, we explored possible compromises, such as how to minimize carrier distortion with low bit error rates. It turned out that the Walsh-Hadamard expansion sequences were best suited for this, and our experiments clearly demonstrated this.