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Optimal Coding and Allocation for Perfect Secrecy in Multiple Clouds

机译:多云中最优保密的最佳编码和分配

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摘要

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.
机译:对于用户来说,将数据存储在云中,使用多个云存储提供商(CSP)提供的服务是提高数据可用性和机密性的一种有前途的方法,因为不同的CSP不太可能同时停止服务或相互勾结以提取用户信息。本文研究了在给定的预算和最小的成本约束下,在多个CSP中可靠,安全地存储数据的问题。先前的工作中,问题表达方式有所不同,通常通过将问题分解成子问题并单独解决来解决问题。尽管这种去耦方法很简单,但最终的解决方案却不是最优的。本文是第一个从整体上考虑该问题并得出联合最优编码和存储分配方案的方案,该方案以最小的成本实现了完美的保密性。分析结果表明,最优编码方案是嵌套的最大距离可分离码,CSP中存储的最优数据量具有一定的结构。可以通过简单的二维搜索以数字方式确定代码的确切参数和每个CSP的确切存储量。

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