A Framework for Data Protection in Cloud Federations

Lena Mashayekhy, Mahyar Movahed Nejad, Daniel Grosu
{"title":"A Framework for Data Protection in Cloud Federations","authors":"Lena Mashayekhy, Mahyar Movahed Nejad, Daniel Grosu","doi":"10.1109/ICPP.2014.37","DOIUrl":null,"url":null,"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.","PeriodicalId":441115,"journal":{"name":"2014 43rd International Conference on Parallel Processing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 43rd International Conference on Parallel Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPP.2014.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

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.
云联盟中的数据保护框架
云计算的好处之一是,云提供商可以通过与其他云提供商组成云联盟来动态地扩展其资源能力。形成云联盟需要考虑数据隐私和安全问题,这对于满足服务水平协议(sla)至关重要。云中隐私和安全挑战的本质要求云提供商设计能够与其资源管理系统协同工作的数据保护机制。在本文中,我们考虑了在云联盟内外包数据和计算时的隐私要求,并提出了一个最小化外包成本的框架,同时考虑了两个关键的数据保护限制,即信任和披露限制。我们将这些限制建模为冲突图,并将问题表述为整数规划。在缺乏计算可处理的最优算法来解决这个问题的情况下,我们设计了一个快速的启发式算法。我们通过大量的实验分析了我们提出的算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信