Image Steganalysis by the Distribution Characters of Stego-images in Reduced Dimension Space

Author

Chen, Guoming ; Zhang, Dong ; Chen, Qiang ; Zhou, Duanning

Author_Institution

Dept. of Comput. Sci., Guangdong Univ. of Educ., Guangzhou, China

fYear

2012

fDate

23-25 Nov. 2012

Firstpage

235

Lastpage

240

Abstract

In this paper we propose an Improved Kernel Linear Discriminant Analysis algorithm to analyze the distribution differences between cover images and stego-images in the reduced dimensional space. We observe that the hidden information, the information hidden in the cover images, of stegoimages are clustered in some plane while all other information of cover-images are scattered more evenly in this space and have no other clusters. Based on this fact, we develop a steganalysis scheme to discriminate stego-images from innocent images. The experiment results show the effectiveness of the proposed approach.

Keywords

image processing; pattern clustering; steganography; cover-image information scattering; hidden information; image steganalysis; innocent images; kernel linear discriminant analysis algorithm; reduced dimension space; stego-image clustering; stego-image distribution characters; Algorithm design and analysis; Clustering algorithms; Educational institutions; Histograms; Kernel; Laplace equations; Vectors; Dimension reduction; data distribution; steganalysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Home (ICDH), 2012 Fourth International Conference on

Conference_Location

Guangzhou

Print_ISBN

978-1-4673-1348-3

Type

conf

DOI

10.1109/ICDH.2012.34

Filename

6376416