标题：A novel cloud data fragmentation cluster-based privacy preserving mechanism
作者：Shao, Yali ;Shi, Yuliang ;Li, Hui
作者机构：[Shao, Yali ;Shi, Yuliang ;Li, Hui ] School of Computer Science and Technology, Shandong University, Jinan, China
来源：International Journal of Grid and Distributed Computing
摘要：SaaS application is becoming more and more popular with the development of the cloud computing. In order to use the cloud service, the tenants should upload their data to the databases of cloud service provider, so how to protect the tenants' privacy information from snooping or leaking by DBA while keeping a good application performance is a big challenge. Therefore, we address this challenge by proposing a novel cloud data fragmentation cluster-based privacy preserving mechanism in this paper, the mechanism could give an optimal privacy preserving strategy by clustering relevancy matrix using Bond Energy Algorithm and partitioning the clustered matrix according to the privacy constraints proposed by the tenants. © 2014 SERSC.