An Effective Ensemble-based Classification Algorithm for High-Dimensional Steganalysis

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Provided by: Academy Publisher
Topic: Security
Format: PDF
Recently, ensemble learning algorithms are proposed to address the challenges of high dimensional classification for steganalysis caused by the curse of dimensionality and obtain superior performance. In this paper, the authors extend the state-of-the-art steganalysis tool developed by the researchers: the Kodovsky's ensemble classifier and propose a novel method, called CSRS for high-dimensional steganalysis. Different from the Kodovsky's ensemble classifier which selects features in a completely random way, the proposed CS-RS modifies the generation method of feature subspaces.
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