Privacy Preserving Data Mining

Privacy is a matter of individual perception, an infallible and universal solution to this dichotomy is infeasible. The common term of privacy in the general, limits the information that is leaked by the distributed computation to be the information that can be learned from the designated output of the computation. The current state-of-the-art paradigm for privacy-preserving data¬†mining is differential privacy, which allows un-trusted parties to access private data through aggregate queries. Privacy Preserving Data Mining :¬†Overview The technology that converts clear text into a non-human readable form is called data anonymization. In recent years data anonymization technique for privacy-preserving data publishing of micro-data has received a lot of attention. Micro-data contains information about an individual entity, such as a person, a household or an organization. In each record a number of attributes can be categorized as i) Identifiers that can uniquely identify an individual, such as Name or Social Security Number ii) some attributes may be Sensitive Attributes (SAs) such as disease and salary and iii) some attributes are Quasi-Identifiers (QI) such as zip code, age, and sex which may be from publicly available database, whose values, when taken together, can potentially identify an individual. Data anonymization enables the transfer…

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