Review on Advanced Cost Effective Approach for Privacy with Dataset in Cloud Storage

Abstract

Cloud computing allows customers to run compute and data-intensive applications without the need for a large investment in infrastructure. Additionally, a significant amount of intermediate datasets are created and often saved, in order to reduce the expense of re-computing these applications. It becomes difficult to protect the privacy of intermediate datasets because attackers may be able to retrieve information that is sensitive to privacy via the analysis of several intermediate datasets. Existing techniques to deal with this problem generally endorse the use of encryption for all cloud datasets. For data-intensive applications, the time and expense of repeatedly decrypting and encrypting intermediate datasets are prohibitive; hence, encrypting all intermediate datasets does not make sense. Big heterogeneous data storage concerns and challenges, countermeasures (security and administration) and cloud storage prospects, are discussed in this article. New questions arise for cloud storage researchers, when they examine these issues in depth.