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JPEG image steganalysis using joint discrete cosine transform domain features

[+] Author Affiliations
Zhihua Xia

Hunan University, School of Computer and Communication, Changsha, 410082, China

Xingming Sun

Hunan University, School of Computer and Communication, Changsha, 410082, China

Wei Liang

Hunan University, School of Computer and Communication, Changsha, 410082, China

Jiaohua Qin

Hunan University, School of Computer and Communication, Changsha, 410082, China and Hunan City University, Department of Mathematics and Computers, Yiyang, 413000, China

Feng Li

Changsha University of Science and Technology, School of Computer and Communication Engineering, Changsha, 410114, China

J. Electron. Imaging. 19(2), 023006 (May 04, 2010). doi:10.1117/1.3421972
History: Received August 18, 2009; Revised January 21, 2010; Accepted March 19, 2010; Published May 04, 2010; Online May 04, 2010
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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.

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© 2010 SPIE and IS&T

Citation

Zhihua Xia ; Xingming Sun ; Wei Liang ; Jiaohua Qin and Feng Li
"JPEG image steganalysis using joint discrete cosine transform domain features", J. Electron. Imaging. 19(2), 023006 (May 04, 2010). ; http://dx.doi.org/10.1117/1.3421972


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