Audio signals containing secret information or not is a security issue addressed in the context of steganalysis. ThRainfalle conceptual ide lies in the difference of the distribution of various statistical distance measures between the cover audio signals and stego-audio signals. The aim of the propose system is to analyze the audio signal which have the presence of information-hiding behavior or not. Mel- frequency ceptral coefficient, zero crossing rate, spectral flux and short time energy features of audio signal are extracted, and combine these features with the features extracted from the modified version that is generated by randomly modifying with significant bits. Moreover, the extracted features are detected or classified with a support vector machine in this propose system. Experimental result show that the propose method performs well in steganalysis of the audio stegnograms that are produced by using S-tools4.
steganalysis, SVM, S-tools4
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