Privacy-preserving certificateless provable data possession scheme for big data storage on cloud

Debiao He, Neeraj Kumar, Huaqun Wang, Lina Wang and Kim-Kwang Raymond Choo

Applied Mathematics and Computation, 2017, vol. 314, issue C, 31-43

Abstract: Cloud storage is generally regarded as one of the most promising technologies to address various big data challenges (e.g. secure storage for big data), due to the capability to provide scalability and functional diversity. However, how to efficiently audit the integrity of outsourced data remains a research challenge. Provable data possession (PDP) scheme can potentially be used to verify the integrity of outsourced data without downloading such data. However, existing PDP schemes suffer from either certificate management or key escrow problems. A number of certificateless PDP (CLPDP) schemes for the public cloud storage have been designed to address the above problems. However, most of them do not offer privacy protection from the verifier (i.e. verifier could obtain the data stored in the cloud when verifying their integrity). In this paper, we propose a privacy-preserving CLPDP (PP-CLPDP) scheme to address certificate management and key escrow problems, as well as ensuring privacy protection. We also prove the security and evaluate the performance of our proposed PP-CLPDP scheme.

Keywords: Public cloud storage; Cloud data integrity; Privacy-preserving; Provable data possession (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:314:y:2017:i:c:p:31-43

DOI: 10.1016/j.amc.2017.07.008

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