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Methods and Systems for Using an Expectation-Maximization (EM) Machine Learning Framework for Behavior-Based Analysis of Device Behaviors

  • US 20170024660A1
  • Filed: 07/23/2015
  • Published: 01/26/2017
  • Est. Priority Date: 07/23/2015
  • Status: Abandoned Application
First Claim
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1. A method of generating behavior classifier models for use in a behavior monitoring system of a computing device, comprising:

  • applying a plurality of behavior vectors that each characterize one of a known normal and a known abnormal behavior to a current classifier model to generate first analysis results;

    using the first analysis results to determine confidence values for classifying each of the plurality of behavior vectors as one of normal and abnormal;

    filtering behavior vectors having confidence values that are above a confidence threshold;

    generating a new classifier model that includes decision nodes that test conditions relevant to the filtered behavior vectors;

    setting the new classifier model as the current classifier model; and

    using the current classifier model in the behavior monitoring system to classify a computing device behavior.

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