Privacy Characterization and Quantification in Data Publishing

Privacy Characterization and Quantification in Data Publishing The increasing interest in collecting and publishing large amounts of individuals’ data to public for purposes such as medical research, market analysis and economical measures has created major privacy concerns about individual’s sensitive information. To deal with these concerns, many Privacy-Preserving Data Publishing (PPDP) techniques have been proposed in literature. However, they lack a proper privacy characterization and measurement. In the proposed model, a novel multi-variable privacy characterization and quantification model is proposed. Based on this model, the prior and posterior adversarial belief…

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