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Keyword-Based Remote Data Integrity Auditing Supporting Full Data Dynamics
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AI
DOI：10.1109/TSC.2023.3339521.png)
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Abstract
En 中文
Remote data integrity auditing, as a key technology for cloud storage, allows verifier to check cloud data integrity without downloading entire file from cloud server (CS). In practice, user might only concern the integrity of the files containing the specific keyword and would like to perform data dynamic operations on data. In this article, we construct a practical keyword-based remote data integrity auditing scheme supporting full data dynamics. In such a scheme, a novel construction called keyword tag is designed. Using the keyword tag, TPA is able to simultaneously check whether CS correctly keeps all files containing the specific keyword. TPA can detect CS's misbehaviors once CS does not keep these files correctly. Furthermore, our scheme supports full data dynamics, including file-level updates and block-level updates. The keyword tag is updated when the user performs the file-level updates. To support block-level updates, we introduce an index switcher set to maintain the relationship between the block index and the authenticator index. We can avoid the recalculation of the authenticators by using authenticator indexes to generate authenticators. After cloud data are updated, data integrity still can be guaranteed. Security analysis and experimental results show that our scheme is provably secure and efficient.
Keywords:
Data integrity
Indexes
Cloud computing
Security
Task analysis
Data privacy
Data models
Cloud storage
data dynamic
data integrity auditing
data security
Journal
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5.8
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2.1K
Citations:
6.5K