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Journal of Electronic Imaging

Steganography forensics method for detecting least significant bit replacement attack
Author(s): Xiaofeng Wang; Chengcheng Wei; Xiao Han
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Paper Abstract

We present an image forensics method to detect least significant bit replacement steganography attack. The proposed method provides fine-grained forensics features by using the hierarchical structure that combines pixels correlation and bit-planes correlation. This is achieved via bit-plane decomposition and difference matrices between the least significant bit-plane and each one of the others. Generated forensics features provide the susceptibility (changeability) that will be drastically altered when the cover image is embedded with data to form a stego image. We developed a statistical model based on the forensics features and used least square support vector machine as a classifier to distinguish stego images from cover images. Experimental results show that the proposed method provides the following advantages. (1) The detection rate is noticeably higher than that of some existing methods. (2) It has the expected stability. (3) It is robust for content-preserving manipulations, such as JPEG compression, adding noise, filtering, etc. (4) The proposed method provides satisfactory generalization capability.

Paper Details

Date Published: 20 January 2015
PDF: 12 pages
J. Electron. Imaging. 24(1) 013016 doi: 10.1117/1.JEI.24.1.013016
Published in: Journal of Electronic Imaging Volume 24, Issue 1
Show Author Affiliations
Xiaofeng Wang, Xi'an Univ. of Technology (China)
Chengcheng Wei, Xi'an Univ. of Technology (China)
Xiao Han, Xi'an Univ. of Technology (China)

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