Non-Linear Data Perturbation Method for Privacy Preserving Data Mining

Abstract

To hold effective data from big databases, Data Mining Methodologies are put on purpose. For recognizing the connections amid the item sets quickly, academicians and researchers are giving attention on the association rule mining amid many different data mining approaches. The subject of privacy matters when the data is spread amongst number of places or sites. The site owner doesn’t desires to supply their data to other sites. But they are involved to have information about global or whole results existed from mining actions. A new representation  is  suggested  which  adopts  mix up  based  protected calculation cryptographic practice considering that whichever locale or site can be dealt as Faithful site to find global association rules for horizontally divided databases.