A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Min Max Normalization Based Data Perturbation Method for Privacy Protection
2013
International journal of computer and communication technology
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. We used data perturbation method for preserving privacy as well as accuracy. In this method individual data value are distorted before data
doi:10.47893/ijcct.2013.1201
fatcat:hcyuqaulgjasfltu5tkrbgsttu