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Systems and methods for personalizing security incident reports

  • US 10,542,017 B1
  • Filed: 10/13/2016
  • Issued: 01/21/2020
  • Est. Priority Date: 10/13/2016
  • Status: Active Grant
First Claim
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1. A computer-implemented method for personalizing security incident reports, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising:

  • generating, within a training dataset, a feature vector for each of a group of security incidents, the feature vector including features that describe the security incidents and the features including response codes that a set of clients assigned to the security incidents as labels;

    training a supervised machine learning function on the training dataset using the response codes that the set of clients assigned to the security incidents such that the supervised machine learning function learns how to predict an assignment of future response codes to future security incidents;

    applying the trained supervised machine learning function to a feature vector that describes a new security incident, as one of the future security incidents, on the set of clients to predict that the set of clients will ignore the new security incident; and

    personalizing a list of security incidents that is electronically reported to the set of clients by deprioritizing the new security incident based on applying the trained supervised machine learning function to the feature vector that describes the new security incident.

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