灵活而安全的云存储企业数据重复数据删除服务

W. Chuan, Shu Qin Ren, S. Keoh, Khin Mi Mi Aung
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引用次数: 4

摘要

云存储服务提供了无限的存储容量和灵活的访问能力,可以存储和共享大规模的内容。由此带来的便利吸引了个人和企业用户将数据服务外包给云提供商。正如调查显示的那样,56%的云存储应用程序用于数据备份,高达68%的数据备份是用户资产。企业租户在将数据上传到云端之前需要保护他们的数据隐私,并期望在云存储、容量和I/ o问题以及系统性能、带宽和数据保护方面降低运营成本的同时获得合理的性能。因此,企业租户既需要安全、经济的数据存储,又需要灵活地访问其云数据。在本文中,我们为企业租户提出了一种安全的重复数据删除解决方案,以利用云存储的优势,同时降低运营成本并保护隐私。首先,该解决方案使用代理进行灵活的组访问控制,支持组内的安全重复数据删除;其次,该解决方案支持可扩展的代理集群,以支持大规模数据访问;第三,该解决方案可以与云存储无缝集成。我们通过集成Drop box来实现和测试我们的解决方案。与明文重复数据删除相比,安全组内重复数据删除的数据传输延迟低,存储开销小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flexible Yet Secure De-duplication Service for Enterprise Data on Cloud Storage
The cloud storage services bring forth infinite storage capacity and flexible access capability to store and share large-scale content. The convenience brought forth has attracted both individual and enterprise users to outsource data service to a cloud provider. As the survey shows 56% of the usages of cloud storage applications are for data back up and up to 68% of data backup are user assets. Enterprise tenants would need to protect their data privacy before uploading them to the cloud and expect a reasonable performance while they try to reduce the operation cost in terms of cloud storage, capacity and I/Os matter as well as systems' performance, bandwidth and data protection. Thus, enterprise tenants demand secure and economic data storage yet flexible access on their cloud data. In this paper, we propose a secure de-duplication solution for enterprise tenants to leverage the benefits of cloud storage while reducing operation cost and protecting privacy. First, the solution uses a proxy to do flexible group access control which supports secure de-duplication within a group, Second, the solution supports scalable clustering of proxies to support large-scale data access, Third, the solution can be integrated with cloud storage seamlessly. We implemented and tested our solution by integrating it with Drop box. Secure de-duplication in a group is performed at low data transfer latency and small storage overhead as compared to de-duplication on plaintext.
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