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k-anonymity is a property possessed by certain anonymized data. The term k-anonymity was first introduced by Pierangela Samarati and Latanya Sweeney in a paper published in 1998, [1] although the concept dates to a 1986 paper by Tore Dalenius. [2]
Latanya Arvette Sweeney is an American computer scientist. She is the Daniel Paul Professor of the Practice of Government and Technology at the Harvard Kennedy School and in the Harvard Faculty of Arts and Sciences at Harvard University. [1]
The concept of K-anonymity was first introduced in relational data privacy to guarantee the usefulness of the data and the privacy of users, when data holders want to release their data. [ 8 ] [ 20 ] [ 21 ] [ 22 ] K-anonymity usually refers to the requirement that the information of the user should be indistinguishable from a minimum of k − 1 ...
The l-diversity model is an extension of the k-anonymity model which reduces the granularity of data representation using techniques including generalization and suppression such that any given record maps onto at least k-1 other records in the data.
According to the EDPS and AEPD, no one, including the data controller, should be able to re-identify data subjects in a properly anonymized dataset. [8] Research by data scientists at Imperial College in London and UCLouvain in Belgium, [ 9 ] as well as a ruling by Judge Michal Agmon-Gonen of the Tel Aviv District Court, [ 10 ] highlight the ...
Datafly algorithm is an algorithm for providing anonymity in medical data. The algorithm was developed by Latanya Arvette Sweeney in 1997−98. [1] [2] Anonymization is achieved by automatically generalizing, substituting, inserting, and removing information as appropriate without losing many of the details found within the data.
The concept of homogeneity can be applied in many different ways and, for certain types of statistical analysis, it is used to look for further properties that might need to be treated as varying within a dataset once some initial types of non-homogeneity have been dealt with.
The Protection of Human Subjects ('Common Rule'), a collection of multiple U.S. federal agencies and departments including the U.S. Department of Health and Human Services, warn that re-identification is becoming gradually easier because of "big data"—the abundance and constant collection and analysis of information along with the evolution ...