Aim: propose a novel multi-variable privacy characterization and quantification model. Existing system: Privacy-Preserving Data Publishing (PPDP) techniques (k-anonymity, l-diversity and t-closeness.) have been proposed in literature. However, they lack a proper privacy characterization and measurement. all the existing PPDP schemes have limitations in privacy characterization Proposed System: PUBLISHING MODEL goals is to quantify privacy loss of individuals having other attribute values (other diseases) within the same class. PRIVACY CHARACTERIZATION proposes two privacy metrics that can measure privacy leakage from two different perspectives. Methodology: The proposed framework consists of two steps . First, model attributes in a dataset as a multi-variable model. Based on first model, are able to re-define the prior and posterior adversarial belief about attribute values of individuals. Then characterize privacy of these individuals based on...
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