抽象的な

A Study on Privacy Preserving Data Mining

K.Sashirekha, B.A.Sabarish, Arockia Selvaraj

Privacy Preserving and Data Mining addresses the problem of protecting the mobile users from the attackers. Privacy threat includes the process of predicting the movement pattern based on the statistical information collected. Intruder monitors the traffic models to predict the group movement and try to access the private information of mobile users. Privacy can be achieved by means of randomization, k-anonymization, and distributed privacy-preserving data mining. In order to provide better privacy multi-level frameworks are used. In this paper, an analysis is done on various methods of privacy preserving and multi-level trust policy, limitation while using large dimension data sets.