Patent ID: 11972023
Assignee: UNIVERSITY OF HELSINKI
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method for creating compatible anonymized data sets, automatically performing with machine learning equipment that operates a machine learning model, the method comprising:
defining data types of individual variables of a first data set;
identifying quasi-identifiers for the first data set;
defining reidentification sensitivity of all or any targeted subset of the individual variables and quasi-identifiers;
defining missing data handling rules for the individual variables;
defining allowed data transformations including generalization and use of synthesized data;
optimizing quasi-identifier selection, use of synthesized data and a choice of data transformations to minimize information loss and maximize privacy metrics based on at least all of:
the first data set;
the allowed data transformations; and
the missing data handling rules;, the method further comprising:
training the machine learning model using: the first data set according to the defined data types; the optimized quasi-identifier selection; the optimized use of synthesized data; and the choice of data transformations;
and anonymizing the first data set using the trained machine learning model.