Privacy and security of big data is emerging as one among the most relevant research challenges of recent years, also stirred-up by a wide family of critical applications ranging from scientific computing to social network analysis and mining, from data stream management to smart cities, and so forth. Traditionally, the issue of making (even very-large) databases private and secure has a long history in the context of encrypted databases but, when specifically considered in the Cloud setting, it poses new requirements and challenges to deal with, with particular regard to the scalability of solutions. In line with this emerging research trend, this paper focuses the attention on state-of-the-art proposals in the area of private databases over Clouds, and proposes critical comments about pros and cons of actual research efforts along with future research directions to be considered in future years.

Private databases on the cloud: Models, issues and research perspectives

CUZZOCREA, Alfredo Massimiliano;
2016

Abstract

Privacy and security of big data is emerging as one among the most relevant research challenges of recent years, also stirred-up by a wide family of critical applications ranging from scientific computing to social network analysis and mining, from data stream management to smart cities, and so forth. Traditionally, the issue of making (even very-large) databases private and secure has a long history in the context of encrypted databases but, when specifically considered in the Cloud setting, it poses new requirements and challenges to deal with, with particular regard to the scalability of solutions. In line with this emerging research trend, this paper focuses the attention on state-of-the-art proposals in the area of private databases over Clouds, and proposes critical comments about pros and cons of actual research efforts along with future research directions to be considered in future years.
9781467390040
9781467390040
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11368/2898233
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