A Survey on Security and Privacy Implications of Privacy Preserving Data Mining

Huge volume of detailed personal data is regularly collected and sharing of these data is proved to be beneficial for data mining application. Such data include shopping habits, criminal records, medical history, credit records etc .On one hand such data is an important asset to business organization and governments for decision making by analyzing it. On the other hand privacy regulations and other privacy concerns may prevent data owners from sharing information fo r data analysis. In order to share data while preserving privacy data owner must come up with a solution which achieves the dual goal of privacy preservation as well as accurate clustering result. The sharing of data is often beneficial in data mining applications. It has been proven useful to support both decision-making processes and to promote social goals. However, the sharing of data has also raised a number of ethical issues. Some such issues include those of privacy, data security, and intellectual property rights. In particular, we address the problem of transforming a database to be shared into a new one that conceals private information while preserving the general patterns and trends from the original database. To address this challenging problem, we propose a unified framework for privacy-preserving data mining that ensures that the mining.