Abstract
Recently, many fruitful results have been presented in text information hiding such as text format-based, text image-based method and so on. However, existing information hiding approaches so far have been very difficult to resist the detecting techniques in steganalysis based on statistical analysis. Based on the Chinese mathematical expression, an efficient method of coverless text information hiding is presented, which is a brand-new method for information hiding. The proposed algorithm directly generates a stego-vector from the hidden information at first. Then based on text big data, a normal text that includes the stego-vector will be retrieved, which means that the secret messages can be send to the receiver without any modification for the stego-text. Therefore, this method is robust for any current steganalysis algorithm, and it has a great value in theory and practical significance.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (NSFC) (61232016, U1405254, 61502242, 61173141, 61173142, 61173136, 61373133), Jiangsu Basic Research Programs-Natural Science Foundation (SBK2015041480), Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology (S8113084001), Open Fund of Demonstration Base of Internet Application Innovative Open Platform of Department of Education (KJRP1402), Priority Academic Program Development of Jiangsu Higher Education Institutions (PADA) Fund, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET) Fund, National Ministry of Science and Technology Special Project Research GYHY201301030, 2013DFG12860, BC2013012.
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Chen, X., Sun, H., Tobe, Y., Zhou, Z., Sun, X. (2015). Coverless Information Hiding Method Based on the Chinese Mathematical Expression. In: Huang, Z., Sun, X., Luo, J., Wang, J. (eds) Cloud Computing and Security. ICCCS 2015. Lecture Notes in Computer Science(), vol 9483. Springer, Cham. https://doi.org/10.1007/978-3-319-27051-7_12
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DOI: https://doi.org/10.1007/978-3-319-27051-7_12
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