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Journal of Electronic Imaging

JPEG image steganalysis using joint discrete cosine transform domain features
Author(s): Zhihua Xia; Xingming Sun; Wei Liang; Jiaohua Qin; Feng Li
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Paper Abstract

A JPEG image steganalysis scheme based on joint discrete cosine transform (DCT) domain features is proposed. Intrinsic characteristics of DCT coefficients, such as histogram, intrablock correlation, and interblock correlation, are exploited to construct three feature sets. Support vector machine is utilized to learn and discriminate the difference of features between cover and stego images. First, the three feature sets are investigated separately to reveal their individual capability of attacking steganographic methods. Second, the feature sets are combined to form a joint feature set with better performance. Experimental results demonstrate that all three feature sets individually succeed in attacking the four typical steganographic tools to some extent, with the intrablock feature set performing the best. Furthermore, the comparison experiments show that the jointed feature set not only outperforms the three individual feature sets but also proves to be better than a previous state-of-the-art steganalysis method.

Paper Details

Date Published: 1 April 2010
PDF: 13 pages
J. Electron. Imag. 19(2) 023006 doi: 10.1117/1.3421972
Published in: Journal of Electronic Imaging Volume 19, Issue 2
Show Author Affiliations
Zhihua Xia, Hunan Univ. (China)
Xingming Sun, Nanjing Univ. of Information Science & Technology (China)
Wei Liang, Hunan Univ. (China)
Jiaohua Qin, Central South Univ. of Forestry and Technology (China)
Feng Li, Changsha Univ. of Science and Technology (China)

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