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Differential privacy and outlier detection within a non-interactive model

  • US 10,445,527 B2
  • Filed: 12/21/2016
  • Issued: 10/15/2019
  • Est. Priority Date: 12/21/2016
  • Status: Active Grant
First Claim
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1. A system comprising:

  • at least one processor; and

    at least one memory storing instructions which, when executed by the at least one processor, cause operations comprising;

    receiving a plurality of indices for a plurality of perturbed data points from an perturbed data set generated by one or more sensors, wherein the plurality of perturbed data points are anonymized versions of a plurality of unperturbed data points with the same plurality of indices, wherein receiving the plurality of indices indicates that the plurality of unperturbed data points are identified as presumed outliers, wherein the plurality of perturbed data points lie around a first center point, and wherein the plurality of unperturbed data points lie around a second center point;

    classifying, based upon distance differences, a first portion of the presumed outliers as true positives, wherein the distance differences include, for each of the plurality of perturbed data points, a difference between a distance of the perturbed data point from the first center point and a distance of a corresponding unperturbed data point from the second center point;

    classifying, based upon the distance differences, a second portion of the presumed outliers as false positives, wherein each presumed outlier is classified as a false positive when a corresponding distance difference for the presumed outlier is less than a threshold distance away from the first center point, and wherein each presumed outlier is classified as a true positive when a corresponding distance difference for the presumed outlier is greater than the threshold distance away from the first center point; and

    providing, based on the classifying, a list of confirmed outliers.

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