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Erschienen in: The Journal of Supercomputing 11/2018

13.08.2018

Privacy-preserving auditing scheme for shared data in public clouds

verfasst von: Libing Wu, Jing Wang, Sherali Zeadally, Debiao He

Erschienen in: The Journal of Supercomputing | Ausgabe 11/2018

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Abstract

Recent advances in cloud storage have enabled users to outsource large amounts of data to a remote cloud server in order to reduce storage and management costs, and share files among many users in a group. However, how to efficiently audit the integrity of shared data while maintaining data privacy and user identity anonymity, is still a critical issue. We propose a novel public auditing scheme for data stored in a remote cloud server and shared among users in a large group. In particular, the proposed scheme incorporates group signature, homomorphic message authentication code to create data block tags, so that it can support public auditing and provide user identity anonymity. Furthermore, we use the random masking technique in the proposed scheme to preserve data privacy from the third-party auditor. The correctness and security analyses demonstrate that the proposed scheme is correct and provably secure under a robust security model. The performance evaluation and experimental results show that the proposed scheme is efficient while maintaining the desirable security properties.

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Metadaten
Titel
Privacy-preserving auditing scheme for shared data in public clouds
verfasst von
Libing Wu
Jing Wang
Sherali Zeadally
Debiao He
Publikationsdatum
13.08.2018
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 11/2018
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-018-2527-y

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