System and method for evaluating marketer re-identification risk
AssigneeUniversity of Ottawa
InventorsKhaled El Emam, Fida Dankar
Life of this patent
Estimating the term…
Abstract
Disclosures of databases for secondary purposes is increasing rapidly and any identification of personal data may from a dataset of database can be detrimental. A re-identification risk metric is determined for the scenario where an intruder wishes to re-identify as many records as possible in a disclosed database, known as a marketer risk. The dataset can be analyzed to determine equivalence classes for variables in the dataset and one or more equivalence class sizes. The re-identification risk metric associated with the dataset can be determined using a modified log-linear model by measuring a goodness of fit measure generalized for each of the one or more equivalence class sizes.
Claims21
A method of assessing re-identification risk of a dataset containing personal information, the method executed by a processor comprising:
- retrieving the dataset comprising a plurality of records from a storage device;
- receiving variables selected from a plurality of variables present in the dataset, wherein the variables may be used as potential identifiers of personal information from the dataset;
- and
- determining equivalence classes for each of the selected variables in the dataset and one or more equivalence class sizes;
- determining a re-identification risk metric associated with the dataset using a modified log-linear model by measuring a goodness of fit measure generalized for each of the one or more equivalence class sizes.
A system for assessing re-identification risk of a dataset containing personal information, the system comprising:
- a memory;
- a processor coupled to the memory, the processor performing:
- retrieving the dataset comprising a plurality of records from the memory;
- receiving variables selected from a plurality of variables present in the dataset, wherein the variables may be used as potential identifiers of personal information from the dataset;
- and
- determining equivalence classes for each of the selected variables in the dataset and one or more equivalence class sizes;
- determining a re-identification risk metric associated with the dataset using a modified log-linear model by measuring a goodness of fit measure generalized for each of the one or more equivalence class sizes.
A computer readable memory containing instructions for assessing re-identification risk of a dataset containing personal information, the instructions when executed by a processor performing:
- retrieving the dataset comprising a plurality of records from the memory;
- receiving variables selected from a plurality of variables present in the dataset, wherein the variables may be used as potential identifiers of personal information from the dataset;
- and
- determining equivalence classes for each of the selected variables in the dataset and one or more equivalence class sizes;
- determining a re-identification risk metric associated with the dataset using a modified log-linear model by measuring a goodness of fit measure generalized for each of the one or more equivalence class sizes.
Dependencies are inferred from the claim text.