Security aware index based quasi–identifier approach for privacy preservation of data sets for cloud applications

Abstract

Privacy preservation is a major task in cloud based applications. Many applications are built in the cloud for their economic benefits and operational convenience. The obtained information in the cloud is often seen as valuable for individuals through malicious intent. There is a lot of personal information and potentially secure data that people stored on their computers, and this information is generally transferred to the cloud. In this document, we propose an efficient index based quasi- identifier approach to ensure privacy preservation and achieve high data utility over incremental and distributed data sets. The modified Fuzzy C Means algorithm is used to construct the clusters by similarity. Anonymised data is retrieved by means of tuple partitioning in the data sets. Analysis results illustrate that the proposed method is more efficient for preserving privacy on incremental data sets than existing approaches. It is implemented in the working platform of Java.