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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Inter-cloud Data Integration System Considering Privacy and Cost
verfasst von : Yuan Tian, Biao Song, Jimupimg Park, Eui-Nam Huh
Erschienen in: Computational Collective Intelligence. Technologies and Applications
Verlag: Springer Berlin Heidelberg
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In spite of all the advantages delivered by cloud computing, still many challenges are hindering the migration of customer software and data into the cloud. Whenever information is shared in the cloud, privacy and security questions may arise. Although many technologies have been proposed in order to meet users’ requirements from privacy concern, however, at the same time, with the increasing number of processed data, the cost for privacy protection also increases dramatically. In this paper, we present a privacy-aware inter-cloud data integration system considering tradeoff between the privacy requirements from users and the charging for those data protection and processing. In contrast to existing data sharing techniques, our method is more practical as the cost for technical supporting privacy must be considered in the commoditized cloud computing environment.