Abstract
The data space for audio signals is large, the correlation is strong, and the traditional encryption algorithm cannot meet the needs of efficiency and safety. To solve this problem, an audio encryption algorithm based on Chen memristor chaotic system is proposed. The core idea of the algorithm is to encrypt the audio signal into the color image information. Most of the traditional audio encryption algorithms are transmitted in the form of noise, which makes it easy to attract the attention of attackers. In this paper, a special encryption method is used to obtain higher security. Firstly, the Fast Walsh–Hadamar Transform (FWHT) is used to compress and denoise the signal. Different from the Fast Fourier Transform (FFT) and the Discrete Cosine Transform (DCT), FWHT has good energy compression characteristics. In addition, compared with that of the triangular basis function of the Fast Fourier Transform, the rectangular basis function of the FWHT can be more effectively implemented in the digital circuit to transform the reconstructed dual-channel audio signal into the R and B layers of the digital image matrix, respectively. Furthermore, a new Chen memristor chaotic system solves the periodic window problems, such as the limited chaos range and nonuniform distribution. It can generate a mask block with high complexity and fill it into the G layer of the color image matrix to obtain a color audio image. In the next place, combining plaintext information with color audio images, interactive channel shuffling can not only weaken the correlation between adjacent samples, but also effectively resist selective plaintext attacks. Finally, the cryptographic block is used for overlapping diffusion encryption to fill the silence period of the speech signal, so as to obtain the ciphertext audio. Experimental results and comparative analysis show that the algorithm is suitable for different types of audio signals, and can resist many common cryptographic analysis attacks. Compared with that of similar audio encryption algorithms, the security index of the algorithm is better, and the efficiency of the algorithm is greatly improved.
Highlights
With the rapid development of the internet, wireless voice communication technology was widely applied in real-life, and in the process of data transmission there is the risk of information leakage; audio information encryption research is of great significance
Using Fast Walsh–Hadamar Transform (FWHT) compression, a one-dimensional signal abandoned in pulse code modulation audio signal data of human hearing is not important, so choosing a suitable one according to the characteristics of audio data-adaptive coefficient of high-energy can reconstruct the original signal [12], which reduces the redundancy of audio signal
A digital audio encryption scheme based on a new Chen memristor chaotic system is proposed to resist various traditional signal attacks
Summary
With the rapid development of the internet, wireless voice communication technology was widely applied in real-life, and in the process of data transmission there is the risk of information leakage; audio information encryption research is of great significance. Zhao H. et al [11] proposed an adaptive symmetric Henon chaotic map, which has the characteristics of wide parameter range and high complexity It has a larger keyspace and is more suitable for encryption algorithms. [18] designed an image encryption algorithm of a new hyperchaotic system based on memristor, which can produce complex chaotic attractors. To improve the security and efficiency of digital speech encryption algorithm, an audio encryption algorithm based on Chen memristor chaotic system is proposed in this paper. The rest of this paper is organized as follows: in Section 2, a new memristor chaotic system model is proposed and the correlation dynamics are analyzed; in Section 3, an encryption algorithm for compressing and denoising audio signals and transforming them into image information is proposed.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
