A Personalized Anonymization Technique Based On An Aggregate Formulation Implemented In Polynomial Time
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2015, Vol 4, Issue 9
Abstract
Differential Privacy makes available a conjectural formulation for solitude that guarantees that the system basically performs the identical way despite of whether any personality is incorporated in the database. In this paper, we deal with both scalability and privacy risk of data anonymization. We recommend a scalable algorithm that meets differential privacy when be appropriate an explicit random sampling. Make known the minimum amount of information or no information at all is undeniable more than ever when organizations try to look after the seclusion of individuals. To accomplish such a purpose, the organizations naturally try to hide from view the uniqueness of an individual to whom data pertains and affect a set of transformations to the micro data previous to liberate it.
Authors and Affiliations
Y Srinivas, D Srinivas
Keywords
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- EP ID EP28248
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