Single Actor Pooled Steganalysis

This paper considers a more practical situation for pooled steganalysis that only a single actor is observed, so that the steganalyst needed to analyze the actor independently without comparing with other actors. We propose a pooled steganalysis method for this situation. For a given actor that has emitted a number of images, feature sets are extracted from each image, respectively, and then feed to a binary classifier popularly used in single object steganalysis. Combining all the results output by the classifier, a final decision is made ensemble to label the given actor as “guilty” or “innocent” with the minimal detection error. Experimental results show that the proposed method is effective for single actor pooled steganalysis.

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