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Discovery routing systems and engines

  • US 10,332,618 B2
  • Filed: 10/05/2018
  • Issued: 06/25/2019
  • Est. Priority Date: 07/26/2013
  • Status: Active Grant
First Claim
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1. A security detection system comprising:

  • a knowledge database programmed to store a plurality of datasets, each dataset comprising at least one descriptor-value pair having a descriptor and an associated value;

    an analytical engine coupled with the knowledge database, and programmed to identify at least one anomaly in a dataset of the plurality of datasets, wherein the at least one anomaly is associated with a condition and characterizes a descriptor-value pair having a value that meets a qualifier associated with the descriptor at or beyond a predetermined threshold value for the descriptor;

    a cross-validation engine comprising an association application and a relationship application, coupled with the analytical engine and programmed to designate the at least one anomaly as a significant anomaly by (i) in the association application, cross-referencing the at least one anomaly with one or more other descriptor-value pairs of attributes that are associated with the condition and known to have a value that meets the qualifier, wherein the cross-referencing includes traversing the plurality of datasets to identify at least one of the one or more other descriptor-value pairs of attributes, (ii) identifying further attributes of the at least one anomaly by performing a comparison of at least one attribute with the at least one value of the descriptor-value pair of the at least one anomaly using at least one parameter different from a parameter of the qualifier, and (iii) in the relationship application, including the descriptor-value pair of the at least one anomaly in a significant anomaly dataset if at least one other descriptor-value pair is identified as related to the condition; and

    an expert engine comprising an expert memory, coupled with the cross-validation engine and programmed to (i) communicate with a plurality of experts, wherein each expert is associated with an identifier in the expert memory, and (ii) associate the descriptor-value pair in the significant anomaly dataset with an expert based on the identifier.

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