Volume 8 Number 3 (Mar. 2013)
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JSW 2013 Vol.8(3): 731-736 ISSN: 1796-217X
doi: 10.4304/jsw.8.3.731-736

Fusion of Two Typical Quantitative Steganalysis Based on SVR

Chunfang Yang1, Fenlin Liu1, Xiangyang Luo1, 2, Ying Zeng1
1Zhengzhou Information Science and Technology Institute, Zhengzhou, China
2State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Science, Beijing, China

Abstract—For the LSB steganography, a fusion method is proposed to fuse two typical quantitative steganalysis methods based on support vector regression (SVR). This paper first gives some main factors influencing the errors of structural steganalysis and weighted stego image steganalysis, viz. the local variance and saturation. Then, the estimated embedding ratios of above two methods, the local variance, the histogram of local variance and saturation are fed to the SVR to train the fusion rule which is used to fusing these two methods. Experimental results show that the proposed fusion method can estimate the embedding ratio with higher accuracy than the individual method.

Index Terms—Steganalysis, fusion, embedding ratio, local variance, support vector regression.


Cite: Chunfang Yang, Fenlin Liu, Xiangyang Luo, Ying Zeng, "Fusion of Two Typical Quantitative Steganalysis Based on SVR," Journal of Software vol. 8, no. 3, pp. 731-736, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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