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细粒度云存储数据完整性检测方法
引用本文:余 星,胡德敏,黄 超.细粒度云存储数据完整性检测方法[J].计算机应用,2014,34(1):27-30.
作者姓名:余 星  胡德敏  黄 超
作者单位:上海理工大学 光电信息与计算机工程学院,上海 200093
基金项目:国家自然科学基金资助项目;上海市教委科研创新项目;上海市教委“晨光计划”项目
摘    要:在云存储服务中,为了使用户能够方便快捷知道其所存在云端服务器上数据的完整性,提出了一种细粒度云存储数据完整性检测方法。将文件分割成文件子块继而分割成基本块,通过引入双线性对和用户随机选择待检测数据块能无限次检测数据的完整性,此外通过可信第三方的引入解决云用户和云供应商纠纷,实现云存储数据的公开验证性。然后给出了所提出方法的正确性和安全性分析,通过实验证明了该方法能较好地检测云存储数据的完整性。

关 键 词:云计算  云存储  数据完整性  数据动态更新  公开验证  
收稿时间:2013-07-18
修稿时间:2013-09-06

Integrity check method for fine-grained cloud storage data
YU Xing HU Demin CHANG Huang.Integrity check method for fine-grained cloud storage data[J].journal of Computer Applications,2014,34(1):27-30.
Authors:YU Xing HU Demin CHANG Huang
Affiliation:School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Abstract:In the cloud storage service, in order to know the integrity of the data stored by users on the cloud server, this paper proposed a check method for the integrity of data fine-grained cloud stored. In the proposed method, the file would be divided into sub-blocks and then basic blocks, and with bilinear pairings and data blocks to be detected selected by users randomly, data integrity could be infinitely detected. Furthermore, by introducing a trusted Third Party Auditor (TPA), the dispute between users and cloud storage provider could be well solved for public validation of cloud storage data. Afterwards, analysis of the correctness and security of the method were given in this paper. Finally, experiments verify that the method is able to detect the data integrity of cloud storage better.
Keywords:cloud computing                                                                                                                          cloud storage                                                                                                                          data integrity                                                                                                                          data dynamic updating                                                                                                                          public validation
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