Abstract
Being easy to understand and simple to implement, substitution technique of performing steganography has gain wide popularity among users as well as attackers. Steganography is categorized into different types based on the carrier file being used for embedding data. The audio file is focused on hiding data in this paper. Human has associated an acute degree of sensitivity to additive random noise. An individual is able to detect noise in an audio file as low as one part in 10 million. Given this limitation, it seems that concealing information within audio files would be a pointless exercise. Human auditory system (HAS) experiences an interesting behavior known as masking effect, which says that the threshold of hearing of one type of sound is affected by the presence of another type of sound. Because of this property, it is possible to hide some data inside an audio file without being noticed. In this paper, the research problem for optimizing the audio steganography technique is laid down. In the end, a methodology is proposed that effectively resolves the stated research problem and finally the implementation results are analyzed to ensure the effectiveness of the given solution.
Highlights
Audio steganography is limited to providing solutions related to copyright and assurance of the integrity of content [1]
MATLAB 2014 is used as the simulation environment. e details regarding secret message embedded, cover audio file, and libraries used are given in the following: (i) Secret message: (i) JPG image of size 8.78 KB and dimension 244 × 250; (ii) PNG image of size 38.6 KB and dimension 512 × 512 (ii) Cover audio: MP4 file of size 5.07 MB and length 3 min 21 sec, bit rate 206 kbps, channels 2, and audio sample rate 44.100 kHz (iii) CODO library: library used for random number generator using chaos theory (iv) social impact theory optimization (SITO) library: library used for optimizer using social impact theory
Peak signal to noise ratio (PSNR) values attained by using proposed work and genetic algorithm (GA) differ in the range of “0” dB to “5” dB maximum
Summary
Audio steganography is limited to providing solutions related to copyright and assurance of the integrity of content [1]. Ese strategies embrace low-bit encoding (LSB), polarity inversion, echo activity, part committal to writing, cepstral activity, sensory activity masking, and spread spectrum [2, 3]. Low-bit encoding (LSB) is the most famous technique, but it suffers from some severe limitations. Because of the higher data hiding capacity of the low-bit encoding substitution technique, its alternate is expected to have similar capacity while maintaining better robustness and imperceptibility. Erefore, there is a requirement for incorporating optimization technique with a steganography method so that the required expectations can be fulfilled effectively [8,9,10,11,12]. 2. Motivation and Scope for Optimization e effectiveness of a steganography technique is analyzed on the parameters, namely, capacity, imperceptibility, and robustness. Low-bit encoding or LSB technique is the most commonly used technique [13,14,15,16,17,18,19]
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