## 1 Introduction  
The fast revolution in communication we are currently experiencing needs faster and more secure means of ensuring the security of audio messages. Nowadays, when everybody has smart-phone in their pocket and at any time has the opportunity to send a different message such as a text or audio message, it is very important to have better options to be more protected. Such fast-paced development is a big challenge when there are many different ways to attack audio data. Audio encryption has applications in online networks, interactive media and healthcare audio systems. Audio files are often larger than image files and common encryption methods such as RSA [1], AES (Rijndael) [2] and Blowfish [3] may not be directly applicable to audio files. The above algorithms require more time and resources when the file is bigger, which makes them inapplicable for audio encryption. In this paper, our focus is on the encryption of wave audio files. Audio encryption refers to the coding of user data in an audio file. The waveform audio file enjoys the benefits of being a famous uncompressed audio file format, developed by IBM and Microsoft. It is a variant of the resource interchange file format (RIFF) and shares its container-based, tagged file structure. The wave file stores the audio recordings with different sampling rates and bitrates in a single container which consists of two sub-containers: the header part and actual sample data part. By using logical XOR, byte audio samples are encrypted with pseudorandom sequences. Because of the resistance of the growing number of statistical attack methods, the use of chaotic maps in encryption schemes is becoming increasingly popular. The chaotic dynamical system includes deterministic systems that exhibit random-like, unpredictable behaviour as a result of their sensitivity depending on the starting values. In Reference [4], a novel audio signal encryption algorithm based on a combination of three chaotic maps was presented. In [5], four different voice signals with different running times were sampled and their values were permuted using the chaotic logistic function and the permuted numbers were further separated into four parts to present the novel audio encryption scheme. The use of chaotic functions and DNA coding to confuse and diffuse audio files was presented in [6]. In [7], a novel compressing sensing-based function to simultaneously compress and encrypt audio files was presented. Novel audio encryption with extensive cryptographic analysis was proposed in [8]. In Reference [9], a novel audio encryption scheme based on the Henon-Tent chaotic pseudo-random number array was proposed. In Reference [10], a noise-tolerant audio encryption technique designed by the application of the \(S_{8}\) symmetric group and chaotic systems was proposed. Steps for audio signal encryption based on the chaotic Henon map were designed in [11]. In [12], a novel three-dimensional chaotic system was proposed for the audio encryption algorithm. Researchers in [13] proposed an algorithm for determining the maximum number of bits that can be used as the generator of a pseudo-random number output including chaos-based functions. In Reference [14], the authors proposed an efficient speech encryption method based on three-dimensional chaotic maps. In [15], the authors presented an audio encryption algorithm using confusion and diffusion based on multi-scroll chaotic function. The motivation of our research was the ever-growing need for more sophisticated and robust encryption due to the evolution of PCs and network technologies. There is a widespread common belief that the chaos-based encryption set of rules allows to reduce the relation among audio content by increasing the cost of the entropy of the encrypted audio as well as lowering the correlation.