CPC G06F 21/6254 (2013.01) [G06F 16/2379 (2019.01)] | 20 Claims |
1. A global partitioning-based method for anonymizing a dataset of biometric data, comprising:
receiving, by an anonymization computer program, a value k representing a number of records to hide a biometric datum among, a value t that represents a t-closeness parameter for a t-close distribution, a weight parameter, and a first number of features to retain for determining an attribute of interest;
receiving, by the anonymization computer program, the attribute of interest;
calculating, by the anonymization computer program, a distribution of the attribute of interest in a biometric dataset;
splitting, by the anonymization computer program, the biometric dataset into a plurality of k-sized clusters that satisfy the t-close distribution;
anonymizing, by the anonymization computer program, each biometric datum in the plurality of k-sized clusters using a weighted average of landmarks for the biometric datums in k-sized clusters using the weight parameter;
adding, by the anonymization computer program, each anonymized biometric datum into an anonymized biometric dataset; and
persisting, by the anonymization computer program, the anonymized biometric dataset.
|