Fine-grained data deletion supporting dynamic data insertion for cloud storage

doi:10.1007/s12083-024-01818-4

2024-11-25

PRE

Changsong Yang *

Yueling Liu

丁勇 (Yong Ding)

DOI：10.1007/s12083-024-01818-4

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摘要

En 中文

Due to the rapid increasing of the total amount of global digital data, cloud storage has gained wide attention from both academia and industry, since it can offer nearly measureless storage spaces to the resource-constraint clients. As a consequence, by employing cloud storage service, clients are able to store massive data on the remote cloud data center. That is, clients can migrate the local heavy storage burden and expensive computation overhead to the cloud data center. Despite plenty of attractive strengths, cloud storage service is consequentially subjected to a few new severe security problems and privacy challenges, such as data deletion, data insertion, and so on. In this article, we focus on a primary but quite important issue, i.e., fine-grained deletion supporting dynamic insertion over cloud data. Specifically, we improve the classical invertible Bloom filter (IBF) and construct a new data validation structure, namely, invertible Bloom filter tree (IBFT). Subsequently, we connect digital signature and IBFT to design a new scheme that can fulfill fine-grained data deletion as well as dynamic data insertion. In our new solution, only client and cloud data center are involved when inserting/deleting cloud data and validating the insertion/deletion consequences, which makes our new solution more practical. At last, we formally analyze the security and implement a prototype system, in which we implement our new proposed solution and evaluate its performance. The experimental consequences prove that contrasted to a few previous solutions, our new solution equipped with more attractive feasibility and efficiency in the real-world applications.

Keyword:

Cloud data

Fine-grained deletion

Dynamic insertion

Invertible bloom filter tree

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