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Mathematical Biosciences & Engineering
Article . 2019 . Peer-reviewed
Data sources: Crossref
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Mathematical Biosciences & Engineering
Article
License: CC BY NC SA
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Steganography in beautified mages

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

Steganography in beautified mages

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.

Related Organizations
Keywords

Informatics, Esthetics, filter image, Reproducibility of Results, distortion function, Image Interpretation, Computer-Assisted, QA1-939, Image Processing, Computer-Assisted, steganography, TP248.13-248.65, Mathematics, Algorithms, Computer Security, Software, Biotechnology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold