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Threshold privacy-preserving cloud auditing with multiple uploaders

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Abstract

Data integrity is a critical security issue in cloud storage. The data integrity checking schemes by a third-party auditor (TPA) have attracted a lot of attention. Sharing data among multiple users (uploaders) is an attractive feature of cloud storage. Considering the scenario of multiple uploaders, privacy-preserving cloud auditing makes it possible for the TPA to publicly verify the data integrity while guarantees that it cannot learn the identity of the data uploader. In this paper, we propose a (t, n)-threshold privacy-preserving auditing scheme. Every user could generate a tag piece of a message from the tag generation algorithm individually. To respond a challenge from the TPA, the server needs at least t tag pieces from different users among all n users. Our scheme does not resort to ring signature or group signature techniques. The tag of a message consists of only one element, which is independent of the number of the users within the group. Therefore, the efficiency of tag generation and auditing of our scheme is compatible with an efficient construction (Wu et al., in: International conference on information security practice and experience ISPEC 2016, Springer, New York, 2016). We use the pairing-based cryptography library (PBC library-0.5.14) to implement the scheme and compare both the computation and transmission cost of our scheme with some existing schemes.

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Notes

  1. This step is to guarantee that the elements in \(pk_\Delta \) are computed from valid shares of w. In practice, an alternative way is to apply a verifiable secret sharing scheme to divide w and compute \(pk_\Delta \).

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Acknowledgements

The authors thank the anonymous reviewers for their invaluable feedback on this work. This research was supported by the National Natural Science Foundation of China (61672289, 61822202, 61872087, 61872089).

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Authors and Affiliations

  1. Institute of Cybersecurity and Cryptology, School of Computing and Information Technology, University of Wollongong, Wollongong, Australia

    Ge Wu, Willy Susilo & Fuchun Guo

  2. Fujian Provincial Key Laboratory of Network Security and Cryptography, Fujian Normal University, Fuzhou, China

    Yi Mu

  3. School of Computer Science and Technology, Nanjing Normal University, Nanjing, China

    Futai Zhang

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  1. Ge Wu
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  2. Yi Mu
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  3. Willy Susilo
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  4. Fuchun Guo
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  5. Futai Zhang
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Correspondence to Yi Mu.

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Wu, G., Mu, Y., Susilo, W. et al. Threshold privacy-preserving cloud auditing with multiple uploaders. Int. J. Inf. Secur. 18, 321–331 (2019). https://doi.org/10.1007/s10207-018-0420-6

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