Multi-keywords carrier-free text steganography based on part of speech tagging

Steganography has attracted more and more attentions in protecting information security. Previous studies achieved by modifying the carriers can't effectively resist the steganalysis methods and attacks. To address this problem, by combining big data with steganography, a novel multi-keywords carrier-free text steganography method based on part of speech tagging is proposed in this paper. In our method, the hidden tags are selected from all the Chinese character components of words. And the POS (Part of Speech) is used to hiding the number of keywords to enhance the hiding capacity. Meanwhile, the redundancy of hidden tags in extraction process is eliminated by ensuring the uniqueness of hidden tags in every stego-text. Also, the way of joint retrieval is used for hiding multi-keywords. The experimental results show that with appropriate hidden tags and large scale of big text data, the proposed method has good performance in the hiding capacity, the success rate of hiding, the extraction accuracy and the time efficiency.