Privacy preserving techniques for storage privacy attacks: A survey

Data mining is a process of extracting knowledge from large amount of data. In recent year privacy preserving data mining has been developed by research community working on knowledge modification and security. The collected data sample may be leaked while residing in storage or stolen anytime during the storing process. Hence protections of such data samples become increasingly important. In this paper we provide a review of preventing such attacks on third parties for the whole lifetime of the samples. We discuss different techniques like randomization method, anonymization method for preserving the privacy of storage data.