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ANOMALY SELECTION USING DISTANCE METRIC-BASED DIVERSITY AND RELEVANCE

  • US 20180241762A1
  • Filed: 02/23/2017
  • Published: 08/23/2018
  • Est. Priority Date: 02/23/2017
  • Status: Active Grant
First Claim
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1. A method comprising:

  • receiving, at a device in a network, a notification of a particular anomaly detected by a distributed learning agent in the network that executes a machine learning-based anomaly detector to analyze traffic in the network;

    computing, by the device, one or more distance scores between the particular anomaly and one or more previously detected anomalies;

    computing, by the device, one or more relevance scores for the one or more previously detected anomalies;

    determining, by the device, a reporting score for the particular anomaly based on the one or more distance scores and on the one or more relevance scores; and

    reporting, by the device, the particular anomaly to a user interface based on the determined reporting score.

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