Title: Privacy preserving file auditing schemes for cloud storage using verifiable random function

Authors: Bharati Mishra; Debasish Jena; Srikanta Patnaik

Addresses: Department of Computer Science and Engineering, IIIT Bhubaneswar, Bhubaneswar, Odisha, India ' Department of Computer Science and Engineering, IIIT Bhubaneswar, Bhubaneswar, Odisha, India ' Department of Computer Science and Engineering, SOA University, Bhubaneswar, Odisha, India

Abstract: Users leverage the cloud storage to store data by uploading files to the cloud storage. They can use it to share files to work on collaborative projects. However, during administrative operations by cloud storage service provider (CSSP), there may be some inadvertent corruption of files during data migration and backup. Due to heavy demands, the cloud service provider may not update the desired files immediately when requested by the owner. As a result, a user of the file may receive an obsolete file. To ensure integrity and freshness of files, third party auditing (TPA) services should be supported by CSSP while maintaining the confidentiality of user files and preserving privacy of users. In this paper, three privacy preserving auditing schemes for files stored in cloud has been proposed. Verifiable random function, merkle hash tree and ciphertext-policy attribute-based encryption has been used to achieve the desired goals.

Keywords: cloud storage; verifiable random function; VRF; merkle hash tree; MHT; auditing.

DOI: 10.1504/IJCNDS.2021.111629

International Journal of Communication Networks and Distributed Systems, 2021 Vol.26 No.1, pp.50 - 75

Received: 29 Aug 2019
Accepted: 13 Nov 2019
Published online: 04 Dec 2020 *

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