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Erschienen in: World Wide Web 4/2020

04.03.2020

Outsourced data integrity verification based on blockchain in untrusted environment

verfasst von: Kun Hao, Junchang Xin, Zhiqiong Wang, Guoren Wang

Erschienen in: World Wide Web | Ausgabe 4/2020

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Abstract

Outsourced data, as the significant component of cloud service, has been widely used due to its convenience, low overhead, and high flexibility. To guarantee the integrity of outsourced data, data owner (DO) usually adopts a third party auditor (TPA) to execute the data integrity verification scheme. However, during the verification process, DO cannot fully confirm the reliability of the TPA, and handing over the verification of data integrity to the untrusted TPA may lead to data security threats. In this paper, we focus on the problem of integrity verification of outsourced data in untrusted environment, that is, how to improve the security and efficiency of data integrity verification without utilizing untrusted TPA. To address the problem, we design a decentralized model based on blockchain consisting of some collaborative verification peers (VPs), each of which maintains a replication of the entire blockchain to avoid maliciously tampering with. Based on the model, we present an advanced data integrity verification algorithm which allows DO to store and check the verification information by writing and retrieving the blockchain. In addition, in order to improve the concurrent performance, we extend the algorithm by introducing the verification group (VG) constituting by some VPs organized by Inner-Group and Inter-Group consensus protocols. We conduct a completed security analysis as well as extensive experiments of our proposed approach, and the evaluation results demonstrate that our proposed approaches achieve superior performance.

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Metadaten
Titel
Outsourced data integrity verification based on blockchain in untrusted environment
verfasst von
Kun Hao
Junchang Xin
Zhiqiong Wang
Guoren Wang
Publikationsdatum
04.03.2020
Verlag
Springer US
Erschienen in
World Wide Web / Ausgabe 4/2020
Print ISSN: 1386-145X
Elektronische ISSN: 1573-1413
DOI
https://doi.org/10.1007/s11280-019-00761-2

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