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Data Outsourcing in Cloud Environments: A Privacy Preserving Approach

机译:云环境中的数据外包:隐私保存方法

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With the increasing cost of maintaining IT centers, organizations are looking into outsourcing thier storage and computational needs to a cloud server. However, such outsourcing has also raised the more serious issue of data privacy. In this paper, we summarize our work in privacy-preserving data outsourcing. In particular, we discuss the issue of employing vertical fragmentation to a relation so that the fragment that is assigned to the cloud server contains maximum data without violating privacy. Here, privacy is expressed in terms of a set of confidentiality constraints. We represent the confidentiality constraints as a graph where the nodes are the attributes and links represent paired confidentiality. We then apply the graph coloring problem with two colors for the a cyclic portion of the graph. We use some heuristic to eliminate the cycles, and complete the coloring of all nodes. We are currently extending the work to multiple relations and constraints with multiple attributes in a constraint (i.e., triplet, quadruplet, etc.) instead of just pairs.
机译:随着维护IT中心的成本越来越大,组织正在研究外包存储和计算需求到云服务器。然而,这种外包也提出了更严重的数据隐私问题。在本文中,我们总结了我们在隐私保留数据外包中的工作。特别是,我们讨论使用垂直碎片到关系的问题,以便分配给云服务器的片段包含最大数据而不违反隐私。在这里,隐私以一组机密性约束表示。我们将机密性约束表示为节点是属性和链接表示成对机密性的图表。然后,我们为图形的循环部分应用了两种颜色的图形着色问题。我们使用一些启发式来消除循环,并完成所有节点的着色。我们目前正在将工作扩展到多个关系和约束中的多个属性(即三联网,四分之一等)而不是成对的。

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