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Multi-keywords carrier-free text steganography based on part of speech tagging

机译:基于语音标记的多关键字无载体文本隐写

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Steganography has attracted more and more attentions in protecting information security. Previous studies achieved by modifying the carriers can't effectively resist the steganalysis methods and attacks. To address this problem, by combining big data with steganography, a novel multi-keywords carrier-free text steganography method based on part of speech tagging is proposed in this paper. In our method, the hidden tags are selected from all the Chinese character components of words. And the POS (Part of Speech) is used to hiding the number of keywords to enhance the hiding capacity. Meanwhile, the redundancy of hidden tags in extraction process is eliminated by ensuring the uniqueness of hidden tags in every stego-text. Also, the way of joint retrieval is used for hiding multi-keywords. The experimental results show that with appropriate hidden tags and large scale of big text data, the proposed method has good performance in the hiding capacity, the success rate of hiding, the extraction accuracy and the time efficiency.
机译:隐写术在保护信息安全方面吸引了越来越多的关注。以前通过修改载体实现的研究无法有效抵抗隐写分析方法和攻击。为了解决这一问题,本文提出了一种将大数据与隐写术相结合的方法,提出了一种基于语音标记的多关键字无载体文本隐写术。在我们的方法中,隐藏标签是从单词的所有汉字成分中选择的。并且POS(词性)用于隐藏关键字的数量,以增强隐藏能力。同时,通过确保每个隐蔽文本中隐藏标签的唯一性,消除了提取过程中隐藏标签的冗余。同样,联合检索的方式也用于隐藏多关键字。实验结果表明,该方法具有适当的隐藏标签和大量的大文本数据,在隐藏容量,隐藏成功率,提取精度和时间效率方面均具有良好的性能。

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