云存储中数据完整性的聚合盲审计方法

何凯; 黄传河; 王小毛; 王晶; 史姣丽

doi:10.11959/j.issn.1000-436x.2015267

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云存储中数据完整性的聚合盲审计方法

学术论文 | 更新时间：2024-06-05

- 云存储中数据完整性的聚合盲审计方法
- Aggregated privacy-preserving auditing for cloud data integrity
- 通信学报 2015年36卷第10期页码：119-132
- 作者机构：
  
  1. 武汉大学计算机学院，湖北武汉 430072
  2. 地球空间信息技术协同创新中心，湖北武汉 430072
- 作者简介：
  
  [ "何凯（1987-），男，湖北黄冈人，武汉大学博士生，主要研究方向为云存储安全等。" ]
  [ "黄传河（1963-），男，湖北随州人，武汉大学教授、博士生导师，主要研究方向为云计算、移动互联网、移动ad hoc网络、无线传感器网络、无线mesh网络、物联网、网络安全、分布并行处理。" ]
  [ "王小毛（1984-），男，湖北天门人，武汉大学博士生，主要研究方向为移动ad hoc网络、计算机图形学等。" ]
  [ "王晶（1986-），女，广西桂林人，武汉大学博士生，主要研究方向为云计算与物联网中的安全与隐私保护。" ]
  [ "史姣丽（1979-），女，山西运城人，武汉大学博士生，主要研究方向为访问控制等。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61373040);国家自然科学基金资助项目(61173137);湖北省自然科学基金资助项目(2010CDA004)
- DOI：10.11959/j.issn.1000-436x.2015267
  中图分类号： TP309
- 网络出版日期：2015-10，
  
  纸质出版日期：2015-10-25
- 稿件说明：
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何凯, 黄传河, 王小毛, 等. 云存储中数据完整性的聚合盲审计方法[J]. 通信学报, 2015,36(10):119-132.

Kai HE, Chuan-he HUANG, Xiao-mao WANG, et al. Aggregated privacy-preserving auditing for cloud data integrity[J]. Journal on communications, 2015, 36(10): 119-132.
何凯, 黄传河, 王小毛, 等. 云存储中数据完整性的聚合盲审计方法[J]. 通信学报, 2015,36(10):119-132. DOI： 10.11959/j.issn.1000-436x.2015267.

Kai HE, Chuan-he HUANG, Xiao-mao WANG, et al. Aggregated privacy-preserving auditing for cloud data integrity[J]. Journal on communications, 2015, 36(10): 119-132. DOI： 10.11959/j.issn.1000-436x.2015267.

摘要

针对云存储中数据完整性问题，提出了一种聚合盲审计方法。利用双线性对映射的性质，在云服务器端将数据证据和标签证据加密后再合并，实现审计者在不知数据内容的情况下进行盲审计。在此基础上，设计高效的索引机制支持数据更新，使数据更新操作不会导致大量额外的计算和通信开销，实现了动态审计。同时，针对多个审计请求，设计将不同的证据聚合的方法，以支持对多所有者多云服务器多文件的批量审计，使批量审计的通信开销与审计请求的数量无关。理论分析和实验结果表明，该方法是可证明安全的，与现有的其他审计方案相比，所提的单审计和批量审计的效率分别提高了21.5%和31.8%。

Abstract

To solve the problem of data integrity in cloud storage

an aggregated privacy-preserving auditing scheme was proposed.To preserve data privacy against the auditor

data proof and tag proof were encrypted and combined by using the bilinearity property of the bilinear pairing on the cloud server.Furthermore

an efficient index mechanism was designed to support dynamic auditing

which could ensure that data update operations did not lead to high additional computation or communication cost.Meanwhile

an aggregation method for different proofs was designed to handle multiple auditing requests.Thus the proposed scheme could also support batch auditing for multiple owners and multiple clouds and multiple files.The communication cost of batch auditing was independent of the number of auditing requests.The theoretical analysis and experimental results show that the proposed scheme is provably secure.Compared with existing auditing scheme

the efficacy of the proposed individual auditing and batch auditing improves 21.5% and 31.8% respectively.

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references

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