Analyzing and Performing Privacy Preserving Data Mining on Medical Databases

For both the production and consumption of data the internet is becoming a standard whereas the security for private data is gradually decreasing. Therefore, to have a safe transaction in the data, security and privacy would be the key issues to be considered. In recent days, privacy has become a key issue in many data mining and knowledge discovery fields which lead to the development of many Privacy Preserving Data Mining (PPDM) techniques. In our work we use few of these techniques to privately preserve the data holder such as hospital data. In this we use techniques named “Anonymization”, “Suppression”, “Generalisation” and “Data Hiding” on different fields for the data to be more secure and project the data which is useful to the public. This is a new way of our approach to create awareness among the public to be more attentive and health conscious. The modified data is clustered based on diseases. Based on the end user requirement the private data of the individual is hidden and the required data is projected.