Min Max Normalization Based Data Perturbation Method for Privacy Protection
Data mining system contain large amount of private and sensitive data such as healthcare, financial and criminal records. These private and sensitive data can not be share to every one, so privacy protection of data is required in data mining system for avoiding privacy leakage of data. Data perturbation is one of the best methods for privacy preserving. The authors used data perturbation method for preserving privacy as well as accuracy. In this method individual data value are distorted before data mining application. In this paper, they present min max normalization transformation based data perturbation.