Speech Steganalysis Based on Multi-classifier Combination

Chenlei Zhang, Junjun Guo
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引用次数: 1

Abstract

Aiming at the problems of low detection rate and high feature dimension in the current steganalysis method based on support vector machine (SVM), a speech steganalysis scheme based on multi-classifier combination is proposed. The steganalysis features are first input into the classifier set, and the first type of prediction results are obtained. Then, the output of the first set of classifiers is taken as the input of the other set of classifiers to get another result.Finally, the two results are processed by the fusion algorithm to obtain a detection result.Based on the feature of pitch delay second-order difference, the proposed steganalysis scheme is evaluated comprehensively, and compared with the existing steganalysis method based on SVM.Experimental results show that this method has better performance than existing steganalysis methods based on SVM.
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基于多分类器组合的语音隐写分析
针对目前基于支持向量机(SVM)的隐写分析方法检测率低、特征维数高的问题,提出了一种基于多分类器组合的语音隐写分析方案。首先将隐写特征输入到分类器集中,得到第一类预测结果。然后,将第一组分类器的输出作为另一组分类器的输入,得到另一个结果。最后,对两个结果进行融合算法处理,得到检测结果。基于基音延迟二阶差分的特点,对所提出的隐写分析方案进行了综合评价,并与现有的基于支持向量机的隐写分析方法进行了比较。实验结果表明,该方法比现有的基于支持向量机的隐写分析方法具有更好的性能。
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