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Text Steganography Based on Ci-poetry Generation Using Markov Chain Model
  • KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Text Steganography Based on Ci-poetry Generation Using Markov Chain Model

Vol. 10, No. 9, September 29, 2016
10.3837/tiis.2016.09.029, Download Paper (Free):

Abstract

Steganography based on text generation has become a hot research topic in recent years. However, current text-generation methods which generate texts of normal style have either semantic or syntactic flaws. Note that texts of special genre, such as poem, have much simpler language model, less grammar rules, and lower demand for naturalness. Motivated by this observation, in this paper, we propose a text steganography that utilizes Markov chain model to generate Ci-poetry, a classic Chinese poem style. Since all Ci poems have fixed tone patterns, the generation process is to select proper words based on a chosen tone pattern. Markov chain model can obtain a state transfer matrix which simulates the language model of Ci-poetry by learning from a given corpus. To begin with an initial word, we can hide secret message when we use the state transfer matrix to choose a next word, and iterating until the end of the whole Ci poem. Extensive experiments are conducted and both machine and human evaluation results show that our method can generate Ci-poetry with higher naturalness than former researches and achieve competitive embedding rate.


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Cite this article

[IEEE Style]
Y. Luo, Y. Huang, F. Li and C. Chang, "Text Steganography Based on Ci-poetry Generation Using Markov Chain Model," KSII Transactions on Internet and Information Systems, vol. 10, no. 9, pp. 4568-4584, 2016. DOI: 10.3837/tiis.2016.09.029.

[ACM Style]
Yubo Luo, Yongfeng Huang, Fufang Li, and Chinchen Chang. 2016. Text Steganography Based on Ci-poetry Generation Using Markov Chain Model. KSII Transactions on Internet and Information Systems, 10, 9, (2016), 4568-4584. DOI: 10.3837/tiis.2016.09.029.