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SYSTEM AND METHOD FOR AUTOMATED MACHINE-LEARNING, ZERO-DAY MALWARE DETECTION

  • US 20140090061A1
  • Filed: 09/26/2013
  • Published: 03/27/2014
  • Est. Priority Date: 09/26/2012
  • Status: Active Grant
First Claim
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1. A method for improved zero-day malware detection comprising:

  • receiving a set of training files which are each known to be either malign or benign;

    partitioning the set of training files into a plurality of categories; and

    training category-specific classifiers that distinguish between malign and benign files in a category of files, wherein the training comprises;

    selecting one of the plurality of categories of training files;

    identifying features present in the training files in the selected category of training files;

    evaluating the identified features to determine the identified features most effective at distinguishing between malign and benign files; and

    building a category-specific classifier based on the evaluated features.

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