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Decision tree induction that is sensitive to attribute computational complexity

  • US 8,495,096 B1
  • Filed: 04/18/2012
  • Issued: 07/23/2013
  • Est. Priority Date: 09/15/2009
  • Status: Active Grant
First Claim
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1. A computer-implemented method for constructing a decision tree for classifying computer files based on the computational complexities of attributes of the files, comprising:

  • creating a plurality of attribute vectors for a plurality of training files, each training file classified as legitimate or malware, and each attribute vector comprising values of a predetermined set of attributes for an associated training file;

    determining a computational complexity score for each attribute in the predetermined set of attributes, the computational complexity score measuring a cost associated with determining a value of an associated attribute for a training file;

    recursively growing the decision tree based on the plurality of attribute vectors and the computational complexity scores; and

    providing the recursively grown decision tree to a client system, the client system adapted to traverse the decision tree to classify a target file at the client system as legitimate or malware.

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