In comparison to the extensive body of existing
\nwork considering publish-once, static anonymization, dynamic
\nanonymization is less well studied. Previous work, most notably
\nm-invariance, has made considerable progress in devising a
\nscheme that attempts to prevent individual records from being
\nassociated with too few sensitive values. We show, however, that
\nin the presence of updates, even an m-invariant table can be
\nexploited by a new type of attack we call the \u201cequivalenceattack.\u201d
\nTo deal with the equivalence attack, we propose a
\ngraph-based anonymization algorithm that leverages solutions
\nto the classic \u201cmin-cut\/max-flow\u201d problem, and demonstrate
\nwith experiments that our algorithm is efficient and effective
\nin preventing equivalence attacks.<\/p>\n","protected":false},"excerpt":{"rendered":"
In comparison to the extensive body of existing work considering publish-once, static anonymization, dynamic anonymization is less well studied. Previous work, most notably m-invariance, has made considerable progress in devising a scheme that attempts to prevent individual records from being associated with too few sensitive values. 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