Abstract
Text information hiding based on synonym substitution is sensitive to synonym dictionary quality. Synonym word forest has a large number of irreplaceable old words, and the network new words are not added, using this dictionary to perform synonym substitution steganography on the carrier text which is easy to change the statistical features of the original text. To solve the above problem, this paper proposed a method that dynamically expands sentiment dictionary. Firstly, we collected and merged the three basic sentiment dictionaries that are widely used and using the conjunction rules to identify the candidate sentiment words. Then the cosine similarity between the sentiment words is calculated by the distributed word vector representation tool Word2vec. The sentiment words have a high similarity value which is added to the sentiment word dictionary. The expanded sentiment dictionary is used as a text information hiding dictionary based on sentiment word substitution, and the 7/3 matrix encoding method is used. Experimental analysis shows that the conjunction rules can effectively identify sentiment words, and the extended sentiment dictionary with 42.8% embedding rate for sentiment word substitution steganography can effectively reduce the possibility of statistical analysis.
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Acknowledgements
We would like to thank the anonymous referees for their careful readings of the manuscripts and many useful suggestions. This work had been co-financed by Natural Science Foundation of China under Grant No. 61472092 and U1405254; Guangdong Provincial Science and Technology Plan Project under Grant No. 2013B010401037.
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Li, F. et al. (2021). A Text Information Hiding Method Based on Sentiment Word Substitution. In: Liu, Q., Liu, X., Li, L., Zhou, H., Zhao, HH. (eds) Proceedings of the 9th International Conference on Computer Engineering and Networks . Advances in Intelligent Systems and Computing, vol 1143. Springer, Singapore. https://doi.org/10.1007/978-981-15-3753-0_72
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DOI: https://doi.org/10.1007/978-981-15-3753-0_72
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