中文摘要：

这份报纸论述一个方法检测在 G.723.1 的隐写术咬了的量子化索引调整(QIM ) 溪流。我们证明在量子化索引顺序的每个量子化索引(codeword ) 的分发失衡并且相关特征。我们在场到摘录的统计模型的图案这些特征的量的特征向量。把提取向量与支持向量机器相结合，我们为在 G.723.1 检测 QIM 隐写术造分类器位溪流。实验证明方法比在一个未压缩的领域提取特征向量的存在盲目察觉方法有远更好的性能。我们的方法的召回和精确都甚至为象 3.6 s 一样低的压缩的位流持续时间是超过 90% 。

英文摘要：

This paper presents a method to detect the quantization index modulation （QIM） steganography in G,723.1 bit stream. We show that the distribution of each quantization index （codeword） in the quantization index sequence has unbalanced and correlated characteristics. We present the designs of statistical models to extract the quantitative feature vectors of these characteristics. Combining the extracted vectors with the support vector machine, we build the classifier for detecting the QIM steganography in G.723.1 bit stream. The experiment shows that the method has far better performance than the existing blind detection method which extracts the feature vector in an uncompressed domain. The recall and precision of our method are all more than 90% even for a compressed bit stream duration as low as 3.6 s.