Techniques for Preserving Privacy in Data Mining for Cloud Storage: A Survey

Abstract

Data is increasing drastically day by day specifically due to the usage of social networking websites like Facebook, Twitter, etc. It is very difficult for data owners to store and manipulate such a huge size of data as it incurs more cost of maintaining resources. To overcome this issue, data owners utilize cloud resources to limit the expenses. But as a third party, the cloud can be curious which may lead to the disclosure of personal data. This led researchers to use some techniques to provide privacy in cloud storage used by data owners and this is referred to as privacy-preserving data mining (PPDM). PPDM preserves the privacy of data owners in the cloud, so the private data remains private even after the mining process. This paper focuses on some of the important PPDM techniques like data distortion, encryption, etc. It brings out an extensive survey of privacy-preserving data mining techniques, their benefits and drawbacks, and put forth the open challenges for further research.