Abstract
The coverless information hiding technology proposed in recent years does not need to modify the carrier image and has good anti-detection ability. However, the existing coverless information hiding technology has the problems of low hiding capacity and poor robustness. To solve this problem, this paper proposed a coverless image information hiding algorithm based on deep convolution feature, which mainly constructs the mapping relationship between image feature and secret information through deep convolution neural network to realize covert communication. Firstly, the sender learns the category features of the image by training the depth convolution neural network, and extracts the depth feature descriptor on this basis. Then, the depth feature descriptor is mapped into a binary sequence to obtain the hash code of each type of image. Finally, according to the inverted quadtree index, the image consistent with the secret information is retrieved for encrypted transmission. After decryption, the receiver inputs the carrier image into the shared deep neural network for classification, and the corresponding class hash code is searched and connected in turn to obtain the secret information. Compared with the traditional method, this method has higher steganography capacity and stronger robustness.
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Acknowledgement
The author would like to thank the support of Central South University of Forestry & Technology and the support of National Science Fund of China.
Funding
This project is supported by the Degree & Postgraduate Education Reform Project of Hunan Province under Grant 2019JGYB154, the Postgraduate Excellent teaching team Project of Hunan Province under Grant [2019]370-133, the National Natural Science Foundation of China under Grant 61772561, the Science Research Projects of Hunan Provincial Education Department under Grant 18A174, the Science Research Projects of Hunan Provincial Education Department under Grant 18C0262 and the Natural Science Foundation of Hunan Province under Grant 2020JJ4141.
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Qin, J., Wang, J., Sun, J., Xiang, X., Xiang, L. (2021). Coverless Image Information Hiding Based on Deep Convolution Features. In: Cai, Z., Li, J., Zhang, J. (eds) Theoretical Computer Science. NCTCS 2021. Communications in Computer and Information Science, vol 1494. Springer, Singapore. https://doi.org/10.1007/978-981-16-7443-3_2
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DOI: https://doi.org/10.1007/978-981-16-7443-3_2
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