Steganalisis pada media audio menggunakan metode Support Vector Machine Radial Basis jiICntion (SVM-Rbf) Classifier
Shelvie Nidya Neyman
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We address the problem of detecting the presence of hidden messages in audio. The detector is based on the characteristics of the denoised residuals of the audio, which may consist of a mixture of speech and music data. A set of generalized moments of the audio signal is measured in terms of objective and perceptual quality measures. The detector discriminates between cover and stego files using a selected subset of features and an Support Vector Machine (SYM) classifier. The proposed scheme achieves on the average 82,5 % discrimination perfomance on individual stegnographic tools. The perfomance for detecting non-embedded hidden messages in audio data is 25 % discrimination. Generally 63,3 % discrimination perfomance is achieved in universal tests. Experimental results show that the proposed tec1mique can be used to detect the presence of hidden messages in digital audio data.
- UT - Computer Science