• Prof.Deepa B. Mane

In today’s global world information is most demanded resource. globally networked society demands sharing of information. The Microdata to be published many times contains sensitive data, publishing such data without proper protection may risky to the individual’s privacy, so must be preserved by Data Publisher before it is published. Research on protecting the privacy of individual’s sensitive data has received contributions from many fields, such as computer science, economics, and social science. Privacy-preserving data publishing (PPDP) balances the fundamental trade-off between individual privacy and the utility of published data. A number of different techniques have recently been used for privacy preserving of multi dimensional data. data anonymization is one of the most important nowadays . Data anonymization techniques, such as generalization, bucketization have been designed. Generalization losses large amount of information when it used for high dimensional data. Bucketization requires separation between quasi attributes with sensitive attributes. So, in this paper we introduce a novel technique called slicing which provides better data utility and preserves privacy.

Anonymization, Microdata release, Data publishing, Data security, Privacy preservation.

"A Review on High Dimensional Data Publication ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.238-243, January-2019, Available :http://www.jetir.org/papers/JETIRW006051.pdf

"A Review on High Dimensional Data Publication ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp238-243, January-2019, Available at : http://www.jetir.org/papers/JETIRW006051.pdf