Steganalysis of AMR Based on Statistical Features of Pitch Delay

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Abstract
The calibrated matrix of the second-order difference of the pitch delay (C-MSDPD) feature has been proven to be effective in detecting steganography based on pitch delay. In this article, a new steganalysis scheme based on multiple statistical features of pitch delay is present. Analyzing the principle of the adaptive multi-rate (AMR) codec, the pitch delay values in the same frame is divided into groups, in each of which, a pitch delay has a closer correlation with the other ones. To depict the characteristic of the pitch delay, two new types of statistical features are adopted in this article. The new features and C-MSDPD feature are together employed to train a classifier based on support vector machine (SVM). The experimental result shows that, the proposed scheme outperforms the existing one at different embedding bit rates and with different speech lengths.

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