Image Complexity and Feature Mining for Steganalysis of Least Significant Bit Matching Steganography
The information-hiding ratio is a well-known metric for evaluating steganalysis performance. In this paper, we introduce a new metric of image complexity to enhance the evaluation of steganalysis performance. In addition, we also present a scheme of steganalysis of least significant bit (LSB) matching steganography, based on feature mining and pattern recognition techniques. Compared to other well-known methods of steganalysis of LSB matching steganography, our method performs the best. Results also indicate that the significance of features and the detection performance depend not only on the information-hiding ratio, but also on the image complexity.
Q. Liu et al., "Image Complexity and Feature Mining for Steganalysis of Least Significant Bit Matching Steganography," Information Sciences, vol. 178, no. 1, pp. 21-36, Elsevier, Jan 2008.
The definitive version is available at https://doi.org/10.1016/j.ins.2007.08.007
Geosciences and Geological and Petroleum Engineering
Keywords and Phrases
Classification; Image Complexity; LSB Matching Steganography; Steganalysis; Computational Complexity; Correlation Theory; Cryptography; Pattern Matching; Information-Hiding Ratio; Data Mining
International Standard Serial Number (ISSN)
Article - Journal
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