Secure Multi Parties Communication using Randomize Group Technique in Privacy Preserving Data Mining

Abstract

the approach which used for extracting the patterns and rules from data is known as data mining. It is also called as Knowledge Discovery from Data or KDD process. Generally data mining approaches are applied on model of dataware house, in which data are collected into central sites and then run the algorithm. The security of private data is the major issue in recent years. Easy availability of personal data raises the issue of privacy preserving data mining. When data is transferred between third parties then it is very necessary to secure that data. Accuracy and privacy of the personal data is important concern in the field of current research. There are several techniques and methods are available for preserve the private data, but development in the fruitful direction provide the accurate and efficient data without any loss. In this way it is very important to develop the techniques in data mining which do the work without sacrifice its privacy concern. To deal with privacy issues of data, Privacy preserving data mining is using. There are many privacy preserving data mining approaches are available to convert the original data. The privacy preserving data mining approaches are examined through its privacy protection degree, accuracy, applicability and efficiency. The proposed research work using randomized group approach for preserving the data in privacy preserving data mining.