Unknown malcode detection using classifiers with optimal training sets
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United States of America Patent
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Jul 8, 2014
Grant Date -
Dec 3, 2009
app pub date -
May 26, 2009
filing date -
May 27, 2008
priority date (Note) -
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Abstract
A method for detecting unknown malicious code is provided. A data set is created, which is a collection of files that includes a first subset with malicious code and a second subset with benign code files, whereas the malicious and benign files are identified by an antivirus program. Subsequently, all files are parsed and a set of top features of all-n grams of the files is selected and reduced by using features selection methods. After determining the optimal number of features, they will be used as training and test sets.
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