Steganography in beautified images

Liyun Liu; Zichi Wang; Zhenxing Qian; Xinpeng Zhang; Guorui Feng; Liyun Liu; Zichi Wang; Zhenxing Qian; Xinpeng Zhang; Guorui Feng

doi:10.3934/mbe.2019116

Mathematical Biosciences and Engineering

2019, Volume 16, Issue 4: 2322-2333. doi: 10.3934/mbe.2019116

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Research article Special Issues

Steganography in beautified images

The authors are with School of Communication and Information Engineering, Shanghai University, Shanghai, 200444, P. R. China.

Received: 02 January 2019 Accepted: 04 March 2019 Published: 15 March 2019

Existing distortion functions in steganography which achieved high undetectability are designed for unprocessed natural image. Nowadays, a large number of images are filtered before transmitting for the sake of beautification. In this situation, existing distortion functions should be improved to fit the properties of these beautified images. This paper proposes a distortion function optimization method for steganography on beautified images. Given an unprocessed image, a popular image beautification software is employed to produce two similar beautified images. One of them is used for embedding and the other one is employed as reference. Guided by the reference, existing distortion functions are improved by distinguishing the embedding costs for ±1 embedding. After embedding, the stego image is closer to the reference, which results in a higher undetectability against steganalysis. Experimental results also proved the increasing of undetectability when examined by modern steganalytic tools.
- steganography,
- filter image,
- distortion function
Citation: Liyun Liu, Zichi Wang, Zhenxing Qian, Xinpeng Zhang, Guorui Feng. Steganography in beautified images[J]. Mathematical Biosciences and Engineering, 2019, 16(4): 2322-2333. doi: 10.3934/mbe.2019116

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Abstract

Existing distortion functions in steganography which achieved high undetectability are designed for unprocessed natural image. Nowadays, a large number of images are filtered before transmitting for the sake of beautification. In this situation, existing distortion functions should be improved to fit the properties of these beautified images. This paper proposes a distortion function optimization method for steganography on beautified images. Given an unprocessed image, a popular image beautification software is employed to produce two similar beautified images. One of them is used for embedding and the other one is employed as reference. Guided by the reference, existing distortion functions are improved by distinguishing the embedding costs for ±1 embedding. After embedding, the stego image is closer to the reference, which results in a higher undetectability against steganalysis. Experimental results also proved the increasing of undetectability when examined by modern steganalytic tools.

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