Unsupervised Steganalysis Based on Artificial Training Sets

2 Mar 2017Daniel Lerch-HostalotDavid Megías

In this paper, an unsupervised steganalysis method that combines artificial training setsand supervised classification is proposed. We provide a formal framework for unsupervisedclassification of stego and cover images in the typical situation of targeted steganalysis (i.e.,for a known algorithm and approximate embedding bit rate)... (read more)

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