Research on Information Hiding Based on Intelligent Creation of Tang Poem

Text is the most important and frequent way for people to exchange information and daily communication in today’s society; thus, text information hiding has great research value and practical significance. This paper explored a novel method of information hiding based on intelligent creation of Tang poem. Based on the construction of meaning intention vocabulary, and by using the recurrent neural network language model, the proposed steganography method can effectively generate carrier Tang poem which confidential information embedded in it. In our method, each line can hide 9-bit sensitive information. The hidden capacity of the five-character Tang poem is 11.25%. Experiments showed that this algorithm had relatively high carrying capacity and concealment.

[1]  Hu Junfeng The Computer Aided Research Work of Chinese Ancient Poems , 2001 .

[2]  Lukás Burget,et al.  Recurrent neural network based language model , 2010, INTERSPEECH.

[3]  Wen-Tai Hsieh,et al.  Natural Language Watermarking Using Semantic Substitution for Chinese Text , 2003, IWDW.

[4]  Enhong Chen,et al.  Chinese Poetry Generation with Planning based Neural Network , 2016, COLING.

[5]  Yong Yi,et al.  Poetry stylistic analysis technique based on term connections , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).

[6]  Maosong Sun,et al.  Generating Chinese Classical Poems with RNN Encoder-Decoder , 2016, CCL.

[7]  Farida Ridzuan,et al.  Text Steganography using Extensions Kashida based on the Moon and Sun Letters Concept , 2017 .

[8]  Mirella Lapata,et al.  Chinese Poetry Generation with Recurrent Neural Networks , 2014, EMNLP.

[9]  Patrick Pantel,et al.  Discovering word senses from text , 2002, KDD.

[10]  Huang Yong-fen Classical Poetry Classification Model Based on Feature Terms Clustered , 2014 .

[11]  Hao,et al.  Research on Information Hiding , 2006 .

[12]  Yongfeng Huang,et al.  Text Steganography Based on Ci-poetry Generation Using Markov Chain Model , 2016, KSII Trans. Internet Inf. Syst..

[13]  Lukás Burget,et al.  Neural network based language models for highly inflective languages , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[14]  P. Urbanovich,et al.  A method of syntactic text steganography based on modification of the document-container aprosh , 2018 .

[15]  Harsh K. Verma,et al.  A high capacity text steganography scheme based on LZW compression and color coding , 2017 .