Abstract: Researching on the impact different steganographic software tools have audio statistical features, revealed the phenomenon that when messages are embedded in a WAV file by using a certain tool, the variation of statistical features in the WAV file which already contains messages embedded by the same tool is abruptly smaller than those in which messages have not been embedded. We call it “negative resonance phenomenon” temporarily. With the phenomenon above and Support Vector Machines (SVMs), we can detect the existence of hidden messages, and also identify the tools used to hide them. As shown by the experimental results, the proposed method can be very effectively used to detect hidden messages embedded by Hide4PGP, Stegowav and S-Tools4.

Key words: Audio steganalysis, Linear prediction, Support Vector Machine (SVM)

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