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Huge volume of data from domain specific applications such as medical,financial, library, telephone, shopping records and individual are regularlygenerated. Sharing of these data is proved to be beneficial for data miningapplication. On one hand such data is an important asset to business decisionmaking by analyzing it. On the other hand data privacy concerns may preventdata owners from sharing information for data analysis. In order to share datawhile preserving privacy, data owner must come up with a solution whichachieves the dual goal of privacy preservation as well as an accuracy of datamining task - clustering and classification. An efficient and effectiveapproach has been proposed that aims to protect privacy of sensitiveinformation and obtaining data clustering with minimum information loss.

Tuple Value Based Multiplicative Data Perturbation Approach To Preserve Privacy In Data Stream Mining