期刊
IEEE SIGNAL PROCESSING LETTERS
卷 26, 期 4, 页码 627-631出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2019.2902095
关键词
Text steganography; text steganalysis; word embedding; word correlation
资金
- National Key Research and Development Program of China [SQ2018YGX210002]
- National Natural Science Foundation of China [U1536207, U1705261, U1636113]
With the rapid development of natural language processing technology in the past few years, the steganography by text synthesis has been greatly developed. These methods can analyze the statistical feature distribution of a large number of training samples, and then generate steganographic texts that conform to such statistical distribution. For these steganography methods, previous steganalysis methods show unsatisfactory detection performance, which remains an unsolved problem and poses a great threat to the security of cyberspace. In this letter, we proposed a fast and efficient text steganalysis method to solve this problem. We first analyzed the correlations between words in these generated steganographic texts. Then, we map each word to a semantic space and used a hidden layer to extract the correlations between these words. Finally, based on the extracted correlation features, we used the softmax classifier to classify the input text. Experimental results show that the proposed model can achieve a high detection accuracy, which shows a state-of-the-art performance.
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