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Fine-Grain Perturbation for Privacy Preserving Data Publishing
2009
2009 Ninth IEEE International Conference on Data Mining
Recent work [12] shows that conventional privacy preserving publishing techniques based on anonymity-groups are susceptible to corruption attacks. In a corruption attack, if the sensitive information of any anonymity-group member is uncovered, then the remaining group members are at risk. In this study, we abandon anonymity-groups and hide sensitive information through perturbation on the sensitive attribute. With each record being perturbed independently, corruption attacks cannot be
doi:10.1109/icdm.2009.98
dblp:conf/icdm/ChaytorWB09
fatcat:33mxmdzwzbaexje5nvwj2mtgui