Steganography Audio Based on Zero-Tree Wavelet Transform Algorithm
Journal Title: Passive Defense - Year 2023, Vol 14, Issue 3
Abstract
Audio steganography is very important, equally steganography in other media (image, video, etc.). In this paper is presented steganography of audio based on embedded zero-tree waveleten transform algorithm. Improving the resistance against white noise and additive noise with the lowest SNR is one of the important topics in steganography. The proposed algorithm is more robust against normal white noise than uniform noise and has a bit error rate of less than 1 bit against SNRs higher than 10db. According to the obtained BER, if the proposed algorithm is attacked, the hidden signal is lost completel. Also, the proposed method is resistant against additive noise. The proposed algorithm has the least changes in the sound smoothness criterion in frequency domain with Capstrom distance scale and audio files in the form of music with soft tone (loudness), and the increase of secret message does not have much effect on creating disturbances in the frequency domain. The proposed algorithm of the frequency spectrum does not change the audio signal much, and it also follows the property of the hearing threshold level, and high-pitched music with male speech has the best results, so it is favorable to the spectrum structure of Bark. Also, the proposed algorithm has favorable results in the time domain. The lowest SNR is related to high-pitched music with female speech, which has an SNR of about 13db. According to the obtained results, we will have the worst case of embedding a secret message by choosing the audio signal with female speech. Because there is a certain smoothness in the fmale speech signal. Therefore, this uniform state will be lost to some extent by embedding a secret message in this type of audio signal, and the CZD criterion will increase according to the component-by-component comparison of the two main signals and the signal containing the secret message.<br /> <br /> <br />
Authors and Affiliations
ٍEsfahani Reza, A. R. Matinfar
Keywords
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- EP ID EP731478
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