This paper introduces the concept of differential privacy (DP) as a novel technical tool that can quantifiably assess the identification #risks of #databases, thereby aiding in the classification of data. By allocating a privacy budget in advance, data controllers can establish auditable and reviewable boundaries between #personal, #anonymous, and #pseudonymous data, while integrating this framework into broader data #riskmanagement practices.
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