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Edge Computing and Blockchain-Based Distributed Audit of Outsourced Dynamic Data

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Abstract

Dynamic outsourced data managed by an untrusted third party is prone to integrity violation. Data auditing is a well-known posterior mechanism to detect integrity violations. Existing integrity auditing schemes are centralized and take significant computation, storage, or communication cost at the data owner. Recently, a distributed auditing scheme involving three parties: the data owner, storage server, and end-users, is proposed. However, it uses redundant failure reports for a corrupt file increases the storage, computation, and communication costs. Also, the low-configured end-users may avoid auditing tasks for efficiency reasons. This paper proposes a secure and efficient distributed auditing scheme for outsourced data that utilizes blockchain and edge computing. The blockchain securely stores distinct failure reports, while edge nodes handle local auditing tasks. The scheme is compared with the existing distributed auditing scheme and found to be secure, and more efficient in terms of computational cost at the data owner and communication cost used by the scheme participants.

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Data Availability

No datasets are generated during and/ or analyzed during the current study. A preliminary version of this paper [36] appeared in the proceedings of ANTS 2022.

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The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Author notes

  1. Amit Kumar Dwivedi, Naveen Kumar and Manik Lal Das have contributed equally to this work.

Authors and Affiliations

  1. SCSET, Bennett University, Greater Noida, U.P., India

    Amit Kumar Dwivedi

  2. Department of CSE, IIIT Vadodara, Gandhinagar, Gujarat, India

    Naveen Kumar

  3. Department of ICT, DA-IICT, Gandhinagar, Gujarat, India

    Manik Lal Das

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  1. Amit Kumar Dwivedi
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  2. Naveen Kumar
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Correspondence to Amit Kumar Dwivedi.

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Dwivedi, A.K., Kumar, N. & Das, M.L. Edge Computing and Blockchain-Based Distributed Audit of Outsourced Dynamic Data. Wireless Pers Commun (2024). https://doi.org/10.1007/s11277-024-11094-3

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