• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A Generation-based Text Steganography by Maintaining Consistency of Probability Distribution

Vol. 15, No. 11, November 30, 2021
10.3837/tiis.2021.11.017, Download Paper (Free):

Abstract

Text steganography combined with natural language generation has become increasingly popular. The existing methods usually embed secret information in the generated word by controlling the sampling in the process of text generation. A candidate pool will be constructed by greedy strategy, and only the words with high probability will be encoded, which damages the statistical law of the texts and seriously affects the security of steganography. In order to reduce the influence of the candidate pool on the statistical imperceptibility of steganography, we propose a steganography method based on a new sampling strategy. Instead of just consisting of words with high probability, we select words with relatively small difference from the actual sample of the language model to build a candidate pool, thus keeping consistency with the probability distribution of the language model. What's more, we encode the candidate words according to their probability similarity with the target word, which can further maintain the probability distribution. Experimental results show that the proposed method can outperform the state-of-the-art steganographic methods in terms of security performance.


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Cite this article

[IEEE Style]
B. Yang, W. Peng, Y. Xue and P. Zhong, "A Generation-based Text Steganography by Maintaining Consistency of Probability Distribution," KSII Transactions on Internet and Information Systems, vol. 15, no. 11, pp. 4184-4202, 2021. DOI: 10.3837/tiis.2021.11.017.

[ACM Style]
Boya Yang, Wanli Peng, Yiming Xue, and Ping Zhong. 2021. A Generation-based Text Steganography by Maintaining Consistency of Probability Distribution. KSII Transactions on Internet and Information Systems, 15, 11, (2021), 4184-4202. DOI: 10.3837/tiis.2021.11.017.

[BibTeX Style]
@article{tiis:25109, title="A Generation-based Text Steganography by Maintaining Consistency of Probability Distribution", author="Boya Yang and Wanli Peng and Yiming Xue and Ping Zhong and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2021.11.017}, volume={15}, number={11}, year="2021", month={November}, pages={4184-4202}}