Paper Details

Now in days, Privacy Preserving Data Mining (PPDM) is the most important area of the Data Mining,which aims to protect the sensitive data comes from different businesses and organizations. Such data is very useful fordata owner to make decision based on the mining result. But the privacy of the data may prevent the data owners fromsharing their data for analysis purpose. The Privacy Preserving Data Mining has become increasingly popular becauseit allows sharing sensitive data for analysis purposes. In this paper we present some key directions in the field of privacypreserving data mining and various dimensions of privacy preserving techniques. We provide a review on piecewisevector quantization approach which segmentized each row of dataset and quantization approach will performed on eachsegment using K-means which later are united to form a transformed dataset.

Chauhan Harshil Narendrabhai, Lolita Singh, “A Review on Privacy Preserving Data Mining Using Piecewise Vector Quantization”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 3, Issue 2, pp. 198-202, February 2016.