Image-Adaptive Steganalysis for LSB Matching Steganography

This paper proposes an image-adaptive steganalysis algorithm for LSB-Matching steganography. In the proposed method, the content features of the input image are analyzed in order to obtain a classification composed by plain and non-plain regions. In this context, only the plain regions of the input image are considered to determine if the image contains or not hidden information. The experimental results show that the proposed steganalysis algorithm outperforms the conventional LSB-Matching steganalysis algorithms in terms of detection performance and the same time minimizes the inter-database error. The results are shown through the ROC curves that illustrate a better performance of the proposed algorithm.