Abstract: Methods and systems to de-identify data records, including to merge pairs of clusters data records of individuals until a number of data records of each cluster meets a minimum size threshold, de-identify the clusters when each cluster meets the minimum size threshold, assess a risk of re-identification of the de-identified clusters based on k-anonymity, increase the minimum size threshold and re-perform the merge, the de-identify, and the assess a risk, if the assessed risk does not meet a risk criterion, and present the de-identified clusters on a display when the assessed risk meets the risk criterion.

Abstract: The present disclosure is related to a method of geo-clustering of data for de-identification of a dataset. The method includes generating a plurality of geoclusters based on a plurality of geocodes. The geocodes may include ZIP codes or postal codes. The method further includes identifying the geoclusters having the smallest population. The geocluster having the smallest population is iteratively merged with the nearest geocluster until a minimum population threshold is met. Once the smallest geocluster meets the minimum population threshold, the plurality of geoclusters can be used to cluster the geocodes within a dataset to be de-identified.

Abstract: System and method to produce an anonymized electronic data product having an individually-determined threshold of re-identification risk, and adjusting re-identification risk measurement parameters based on individual characteristics such as geographic location, in order to provide an anonymized electronic data product having a sensitivity-based reduced risk of re-identification.