Improving efficiency of remote data audit for cloud storage

被引:1
|
作者
Fan, Kuan [1 ]
Liu, Mingxi [2 ]
Shi, Wenbo [1 ]
机构
[1] Northeastern Univ, Sch Comp & Commun Engn, Qinhuangdao 066000, Hebei, Peoples R China
[2] Northeastern Univ, Sch Comp & Commun Engn, Shenyang 110819, Liaoning, Peoples R China
基金
中国国家自然科学基金;
关键词
Cloud storage; PPS; public auditing; auditing result statistics; BIG DATA;
D O I
10.3837/tiis.2019.04.026
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The cloud storage service becomes a rising trend based on the cloud computing, which promotes the remote data integrity auditing a hot topic. Some research can audit the integrity and correctness of user data and solve the problem of user privacy leakage. However, these schemes cannot use fewer data blocks to achieve better auditing results. In this paper ,we figure out that the random sampling used in most auditing schemes is not well apply to the problem of cloud service provider (CSP) deleting the data that users rarely use, and we adopt the probability proportionate to size sampling (PPS) to handle such situation. A new scheme named improving audit efficiency of remote data for cloud storage is designed. The proposed scheme supports the public auditing with fewer data blocks and constrains the server's malicious behavior to extend the auditing cycle. Compared with the relevant schemes, the experimental results show that the proposed scheme is more effective.
引用
收藏
页码:2198 / 2222
页数:25
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