Steganalysis of AMR Based on Statistical Features of Pitch Delay

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Author(s): Yanpeng Wu (Xiamen Meiya Pico Information Co., Ltd., Xiamen, China), Huiji Zhang (Xiamen Meiya Pico Information Co., Ltd., Xiamen, China), Yi Sun (Xiamen Meiya Pico Information Co., Ltd., Xiamen, China) and Minghui Chen (Xiamen Meiya Pico Information Co., Ltd., Xiamen, China)
Copyright: 2019
Volume: 11
Issue: 4
Pages: 16
Source title: International Journal of Digital Crime and Forensics (IJDCF)
Editor(s)-in-Chief: Feng Liu (Chinese Academy of Sciences, China)
DOI: 10.4018/IJDCF.2019100105

Keywords: Digital Crime & Forensics / Information Science Reference / IT Security and Ethics / Security & Forensics

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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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Steganalysis of AMR Based on Statistical Features of Pitch Delay

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