DocumentCode
154140
Title
A Framework for Data Protection in Cloud Federations
Author
Mashayekhy, Lena ; Nejad, Mahyar Movahed ; Grosu, Daniel
Author_Institution
Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA
fYear
2014
fDate
9-12 Sept. 2014
Firstpage
283
Lastpage
290
Abstract
One of the benefits of cloud computing is that a cloud provider can dynamically scale-up its resource capabilities by forming a cloud federation with other cloud providers. Forming cloud federations requires taking the data privacy and security concerns into account, which is critical in satisfying the Service Level Agreements (SLAs). The nature of privacy and security challenges in clouds requires that cloud providers design data protection mechanisms that work together with their resource management systems. In this paper, we consider the privacy requirements when outsourcing data and computation within a federation of clouds, and propose a framework for minimizing the cost of outsourcing while considering two key data protection restrictions, the trust and disclosure restrictions. We model these restrictions as conflict graphs, and formulate the problem as an integer program. In the absence of computationally tractable optimal algorithms for solving this problem, we design a fast heuristic algorithm. We analyze the performance of our proposed algorithm through extensive experiments.
Keywords
cloud computing; data privacy; graph theory; integer programming; SLA; cloud computing; cloud federation; conflict graph; data privacy; data protection; data security; disclosure restriction; integer programming; resource management system; service level agreement; trust restriction; Algorithm design and analysis; Cloud computing; Data privacy; Measurement; Outsourcing; Partitioning algorithms; Security; cloud computing; data protection; federation formation; virtual machine placement;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel Processing (ICPP), 2014 43rd International Conference on
Conference_Location
Minneapolis MN
ISSN
0190-3918
Type
conf
DOI
10.1109/ICPP.2014.37
Filename
6957237
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