Preserving privacy in collaborative data publishing from heterogeneity attack

Abstract

Collaborative data publishing means the data are distributed among multiple data providers or data owners. In this main concern is while publishing data preserving individual's privacy. While publishing collaborative data to multiple data providers two types of problem occurs, first is outsider attack and second is insider attack. Outsider attack is performed by people who are not data providers where as insider attack is performed by colluding data provider who may use their own data records to get the data records shared by other data providers. Insider attack is performed by people who are data provider or data owner. In this paper to overcome the problem of such attacks in collaborative data publishing the encryption strategy can be used such as 3DES which provides individuals data protection by using three keys. And again performing encryption on key with MD5 algorithm and appending it to the block of data.