Data mining may be a well-known technique for automatically and intelligently extracting data or data from a large quantity of information. Data processing, the extraction of hidden predictive information from large databases, may be a new technology with nice potential to assist corporations target the most necessary data in their information warehouses Privacy preserving data processing may be an analysis space involved with the privacy driven from in person recognizable data once considered for data processing. Therefore, PPDM has become a progressively necessary field of analysis. PPDM may be a novel analysis direction in data processing. Variety of strategies and techniques are developed for privacy conserving data processing.
As Previous work in work is done for generalization and suppression of numeric value without knowing that it is required to perturb that data or not. So proposed model first generate association rules from set of textual data as well as numeric one. Then those rules which cross some minimum support value is consider as the sensitive rule for hiding. Then perturbation of non homogenous attribute is done by generalization.
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