A global partitioning-based method for anonymizing a dataset of biometric data may include an anonymization computer program: (1) receiving 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; (2) receiving the attribute of interest; (3) calculating a distribution of the attribute of interest in a biometric dataset; (4) splitting the biometric dataset into a plurality of k-sized clusters that satisfy the t-close distribution; (5) anonymizing 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; (6) adding each anonymized biometric datum into an anonymized biometric dataset; and (7) persisting the anonymized biometric dataset.