Privacy Preservation Of The Field Of Data Mining

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Data Mining is an analytic process designed to explore data (usually large amounts of data - typically business or market related - also known as "big data") in search of consistent patterns and systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data. In recent years, with the tremendous development in the internet, data storage and processing technologies, privacy and security has become our major concerns in the field of data mining. Privacy preservation is one of the most important and challenging factor as the sensitive data should not be embarrassed by the adversery.this paper presents wide survey of different privacy preserving techniques and algorithms for privacy preserving data mining and points out the merits and demerits.

Different approaches of privacy preservation:
In this era where internet is everything, for any purpose the corporations have to maintain large amounts of electronic data, therefore privacy of data has become our major concern .the main aim of privacy preservation is utilization of enormous amount of data present without harming the individual’s privacy. There are many effective algorithms for privacy preserving data mining but in all the approaches, some form of transformations are applied to the data in order preserve its privacy. Many methods reduce the granularity in representation in order to reduce the privacy. The transformed data set is made available

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