Optimizing the Convergence of Data Utility and Privacy in Data Mining
Data mining plays a vital role in today's information world where it has been widely applied in various organizations. The current trend needs to share data for mutual benefit. However, there has been a lot of concern over privacy in the recent years. It has also raised a potential threat of revealing sensitive data of an individual when the data is released publically. Various methods have been proposed to tackle the privacy preservation problem like anonymization, perturbation, generalization and l-diversity. But the natural consequence of privacy preservation is information loss.