Enlu Li1, Zhangjie Fu1,2,3,*, Siyu Chen1, Junfu Chen1
Journal of Cyber Security, Vol.2, No.4, pp. 183-190, 2020, DOI:10.32604/jcs.2020.015010
Abstract With the development of natural language processing, deep learning,
and other technologies, text steganography is rapidly developing. However,
adversarial attack methods have emerged that gives text steganography the ability
to actively spoof steganalysis. If terrorists use the text steganography method to
spread terrorist messages, it will greatly disturb social stability. Steganalysis
methods, especially those for resisting adversarial attacks, need to be further
improved. In this paper, we propose a two-stage highly robust model for text
steganalysis. The proposed method analyzes and extracts anomalous features at
both intra-sentential and inter-sentential levels. In the first phase, every sentence
is first transformed into… More >
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