一种改进的基于同义词替换的中文文本信息隐藏方法

通过深入分析当前针对中文的基于同义词替换的自然语言信息隐藏算法，发现由于存在大量不完全可替换的同义词词组，经过同义词替换后可能会破坏句子的语义一致性，针对这一缺点，提出了一种改进的基于同义词替换的中文文本信息隐藏算法，该算法利用知网对同义词词组进行分类，对于不完全可替换的同义词词组，通过依存句法分析来获取同义词的上下文搭配词语，根据搭配词语判断是否进行替换，实验结果表明，该算法能有效地排除错误的同义词替换，替换的准确率达到89.1％。

An improved steganographic algorithm based on synonymy substitution for chinese text

Because of the existence of a large number of non-totally interchangeable synonymy sets, the present natural language steganographic approaches based on Chinese synonymy substitution may destroy the semantic coherence after synonymy substitutions. To deal with this disadvantage, this paper proposes an improved steganographic algorithm based on synonymy substitution for Chinese text. First, the algorithm classifies the synonymy sets with HowNet. For the non-totally interchangeable synonymy sets, the collocational words of the synonymy are acquired from the context by the dependency relationship analysis. And then according to the collocational words it can be determined whether to do the substitution. As shown by the experimental results, the algorithm can effectively avoid the wrong synonymy substitutions, and the accuracy rate of substitution can reach 89. 1%.