Determining journalist risk of a dataset using population equivalence class distribution estimation
AssigneePrivacy Analytics Inc.
InventorsStephen Korte, Luk Arbuckle, Andrew Baker, Khaled El Emam, Sean Rose
Life of this patent
Estimating the term…
Abstract
A system, method and computer readable memory for determining journalist risk of a dataset using population equivalence class distribution estimation. The dataset may be a cross-sectional data set or a longitudinal dataset. The determine risk of identification can be determined and used in de-identification process of the dataset.
Claims21
A method of determining a journalist risk associated with a longitudinal dataset having personal data, including quasi-identifiers, of individuals representing a sample of a population in a database, the method comprising, on a computing device:
- determining, from cross-sectional data in the longitudinal dataset for each of the individuals represented in the sample, a similarity measure;
- rounding the similarity measure to an integer value, wherein using a combinatorics approach, the integer value of the rounded similarity measure directly translates to a respective one of equivalence classes, each including a subset of the individuals having identical values for all the quasi-identifiers, each subset having a subset size;
- and
- for each of the equivalence classes:
- obtaining a sample equivalence class distribution by dividing the rounded similarity measure by the determined similarity measure, wherein the obtained sample equivalence class distribution is a population equivalence class distribution;
- calculating a probability that the equivalence class of a first size comes from population of the equivalence class of a second size;
- calculating an average prosecutor risk, without consideration of the population, by dividing a proportion of the individuals that belong to the equivalence class by the subset size of the equivalence class and summing the result;
- determining the journalist risk by multiplying the proportion of the individuals that belong to the equivalence class by the calculated probability;
- de-identifying the database based on the journalist risk to provide a de-identified database;
- and
- displaying the journalistic risk on a display of the computing device.
A system to determine a journalist risk associated with a longitudinal dataset having personal data, including quasi-identifiers, of individuals representing a sample of a population in a database, the system comprising a processor configured to:
- determine, from cross-sectional data in the longitudinal dataset for each of the individuals represented in the sample, a similarity measure;
- round the similarity measure to an integer value, wherein using a combinatorics approach, the integer value of the rounded similarity measure directly translates into a respective one of equivalence classes, each including a subset of the individuals having identical values for all the quasi-identifiers, each subset having a subset size;
- and
- for each of the equivalence classes:
- obtain a sample equivalence class distribution by dividing the rounded similarity measure by the determined similarity measure, wherein the obtained sample equivalence class distribution is a population equivalence class distribution;
- calculate a probability that the equivalence class of a first size comes from population of the equivalence class of a second size;
- calculate an average prosecutor risk, without consideration of the population, by dividing a proportion of the individuals that belong to the equivalence class by the subset size of the equivalence class and summing the result;
- determine the journalist risk by multiplying the proportion of records that belong to the equivalence class by the calculated probability;
- de-identify the database based on the journalist risk to provide a de-identified database;
- and
- displaying the journalistic risk on a display associated with the processor.
A non-transitory computer readable medium encoded with a computer program to determine a journalist risk associated with a longitudinal dataset having personal data, including quasi-identifiers, of individuals representing a sample of a population in a database, wherein the computer program comprises instructions to cause a processor to:
- determine, from cross-sectional data in the longitudinal dataset for each of the individuals represented in the sample, a similarity measure;
- round the similarity measure to an integer value, wherein using a combinatorics approach, the integer value of the rounded similarity measure directly translates into a respective one of equivalence classes, each including a subset of the individuals having identical values for all the quasi-identifiers, each subset having a subset size;
- and
- for each of the equivalence classes:
- obtain a sample equivalence class distribution by dividing the rounded similarity measure by the determined similarity measure, wherein the obtained sample equivalence class distribution is a population equivalence class distribution;
- calculate a probability that the equivalence class of a first size comes from population of the equivalence class of a second size;
- calculate an average prosecutor risk, without consideration of the population, by dividing a proportion of the individuals that belong to the equivalence class by the subset size of the equivalence class and summing the result;
- determine the journalist risk by multiplying the proportion of records that belong to the equivalence class by the calculated probability;
- de-identify the database based on the journalist risk to provide a de-identified database;
- and
- display the journalistic risk on a display associated with the processor.
Dependencies are inferred from the claim text.