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Improvement of Steganalysis Using Multiplication Noise Addition  

Park, Tae-Hee (Dept. Mechatronics Eng., TongMyong University)
Eom, Il-Kyu (Dept. Mechatronics Eng., TongMyong University)
Publication Information
Abstract
This paper proposes an improved steganalysis method to detect the existence of secret message. Firstly, we magnify the small stego noise by multiplying the speckle noise to a given image and then we estimate the denoised image by using the soft thresholding method. Because the noises are not perfectly eliminated, some noises exist in the estimated cover image. If the given image is the cover image, then the remained noise will be very small, but if it is the stego image, the remained noise will be relatively large. The parent-child relationship in the wavelet domain will be slighty broken in the stego image. From this characteristic, we extract the joint statistical moments from the difference image between the given image and the denoised image. Additionally, four statistical moments are extracted from the denoised image for the proposed steganalysis method. All extracted features are used as the input of MLP(multilayer perceptron) classifier. Experimental results show that the proposed scheme outperforms previous methods in terms of detection rates and accuracy.
Keywords
steganalysis; speckle noise; parent-child relationship; joint characteristic function; MLP;
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