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Adaptive-capacity and robust natural language watermarking for agglutinative languages

机译:凝集语言的自适应能力和强大的自然语言水印

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We present a robust and adaptive-capacity watermarking algorithm for agglutinative languages. All processes, including the selection of sentences to be watermarked, watermark embedding, and watermark extraction, are based on syntactic dependency trees. We show that it is more robust to use syntactic dependency trees than the surface forms of sentences in text watermarking. For the agglutinative languages, we embed watermark using the two main characteristics of the languages. First, because a word consists of several morphemes, we can watermark sentences using morphological division/combination without deep linguistic analysis. Second, they permit relatively free word order, so we can move a syntactic constituent within its clause. Finally, to increase the information-hiding capacity, we adaptively compute the number of watermark bits to be embedded for each sentence. We perform three kinds of evaluation: perceptibility, robustness, and capacity of our method. High capacity is achieved by dynamically determining possibly embedded watermark bits for each sentence. The secret rank based on a syntactic dependency tree strengthens robustness of our method. Finally, we show that the displacement of syntactic constituents and morphological division/combination does not affect the style and naturalness of the text.
机译:我们为凝集语言提供了一种鲁棒的自适应容量水印算法。所有过程(包括要加水印的句子的选择,水印嵌入和水印提取)均基于语法相关性树。我们表明,在文本水印中使用句法依赖树比句子的表面形式更健壮。对于凝集语言,我们使用语言的两个主要特征来嵌入水印。首先,因为一个单词由几个词素组成,所以我们可以使用词法划分/组合为句子加水印,而无需进行深入的语言分析。其次,它们允许相对自由的词序,因此我们可以在其子句中移动语法成分。最后,为了提高信息隐藏能力,我们自适应地计算每个句子要嵌入的水印位的数量。我们执行三种评估:方法的可感知性,鲁棒性和能力。通过动态确定每个句子可能嵌入的水印位来实现高容量。基于句法依赖树的秘密等级增强了我们方法的鲁棒性。最后,我们表明语法成分的移位和形态划分/组合不会影响文本的样式和自然性。

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