In real world many organizations deal with large amount of data, which are the private information collected from individuals. They need to provide security measures to the private data, to provide the results without revealing private information. Many individuals are afraid of exposing their own information and give false inputs and the organizations should be careful about when and where to expose the privacy information and provide security controls. This is how the privacy preserving data mining has become more popular in recent years. In this paper we discuss about various privacy preserving data mining models and also provide comparative study on it. Measuring different techniques, the authors propose that secure multiparty computation mechanism is the best solution for protecting the private information.