In this paper, we propose a new multi-class steganalysis for binary image. The proposed method can identify the type of steganographic technique used by examining on the given binary image. In addition, our proposed method is also capable of differentiating an image with hidden message from the one without hidden message. In order to do that, we will extract some features from the binary image. The feature extraction method used is a combination of the method extended from our previous work and some new methods proposed in this paper. Based on the extracted feature sets, we construct our multi-class steganalysis from the SVM classifier. We also present the empirical works to demonstrate that the proposed method can effectively identify five different types of steganography. © Springer-Verlag Berlin Heidelberg 2010.
CITATION STYLE
Chiew, K. L., & Pieprzyk, J. (2010). Binary image steganographic techniques classification based on multi-class steganalysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6047 LNCS, pp. 341–358). https://doi.org/10.1007/978-3-642-12827-1_25
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