Steganography forensics method for detecting least significant bit replacement attack

Xiaofeng Wang; Chengcheng Wei; Xiao Han

doi:10.1117/1.JEI.24.1.013016

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.

Citation Download Citation

Xiaofeng Wang, Xiaofeng Wang, Chengcheng Wei, Chengcheng Wei, Xiao Han, Xiao Han, } "Steganography forensics method for detecting least significant bit replacement attack," Journal of Electronic Imaging 24(1), 013016 (20 January 2015). https://doi.org/10.1117/1.JEI.24.1.013016 . Submission:

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