In recent years, advances in hardware technology have led to an increase in the capability to store and record personal data about consumers and individuals. This has led to concerns that the personal data may be misused for a variety of purposes. In order to alleviate these concerns, a number of techniques have recently been proposed in order to perform the data mining tasks in a privacy-preserving way. These techniques for performing privacy preserving data mining are drawn from a wide array of related topics such as data mining, cryptography and information hiding. This approach converts the original sample data sets into a group of unreal data sets, from which the original samples cannot be reconstructed without the entire group of unreal data sets.