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|Web of Science®
|Optimal coding and allocation for perfect secrecy in multiple clouds
Wan Sung, C.
|IEEE Transactions on Information Forensics and Security, 2016; 11(2):388-399
|Ping Hu, Chi Wan Sung, Siu-Wai Ho, and Terence H. Chan
|For a user to store data in the cloud, using services provided by multiple cloud storage providers (CSPs) is a promising approach to increase the level of data availability and confidentiality, as it is unlikely that different CSPs are out of service at the same time or collude with each other to extract information of a user. This paper investigates the problem of storing data reliably and securely in multiple CSPs constrained by given budgets with minimum cost. Previous works, with variations in problem formulations, typically tackle the problem by decoupling it into sub-problems and solve them separately. While such a decoupling approach is simple, the resultant solution is suboptimal. This paper is the first one which considers the problem as a whole and derives a jointly optimal coding and storage allocation scheme, which achieves perfect secrecy with minimum cost. The analytical result reveals that the optimal coding scheme is the nested maximum-distance-separable code and the optimal amount of data to be stored in the CSPs exhibits a certain structure. The exact parameters of the code and the exact storage amount to each CSP can be determined numerically by simple 2-D search.
|Cloud storage; perfect secrecy; information-theoretic security; storage allocation
|Date of publication November 12, 2015; date of current version December 10, 2015.
|© 2015 IEEE.
|Appears in Collections:
|Aurora harvest 4
Electrical and Electronic Engineering publications
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