Efficient k -Anonymization Using Clustering Techniques

By Ji-Won Byun, Ashish Kamra, Elisa Bertino, Ninghui Li. International Conference on Database Systems for Advanced Applications, 2007

350 citations recorded by the source corpus.

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Data and Structural k-Anonymity in Social Networks (2009, methodology): “In this section we compare the SaNGreeA algorithm and the anonymization algorithm proposed in [31], which is based on collapsing clusters as formed by any classical k-anonymization algorithm for microdata [4,13].”
Security Services Using Blockchains: A State of the Art Survey (2018, neutral): “at least K-1 other records [53].”
On sampling, anonymization, and differential privacy or, k-anonymization meets differential privacy (2011, background): “Consider the following anonymization scheme, which represents several proposed algorithms for k-anonymity [5, 21].”
Application of Local Differential Privacy to Collection of Indoor Positioning Data (2018, background): “For example, [1], [2] group k similar records into a cluster and generalize each cluster to achieve k-anonymity.”