Extracting Relevant Features of Steganographic Schemes by Feature Selection Techniques
نویسندگان
چکیده
This paper presents a methodology for steganalysis based on a set of 193 features with two main goals. The first goal is to determine a sufficient number of images for effective training of a classifier in the obtained high-dimensional space. Second goal is to use feature selection to select most relevant features for the desired classification. Dimensionality reduction is performed using a forward selection and reduces the original 193 features set by a factor of 13, with overall same performance. Additionally, two new tools are proposed for feature selection in order to validate and possibly analyze further the current results.
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تاریخ انتشار 2007