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An alternative approach to public cloud data auditing supporting data dynamics

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Abstract

Public cloud data auditing allows a user to delegate an auditing job to a third party who is responsible for verifying whether a cloud server has faithfully stored a file or not. Proof of retrievability (PoR) is a widely used protocol for this kind of job. To the best of our knowledge, in the publicly verifiable setting with supporting data dynamics, all known PoR schemes are either rely on the random oracles or are built in the standard model but require nonstandard assumptions. In this paper, we present a scheme which explores the linear homomorphic signature and the sequence Merkle hash tree to construct the homomorphic linear authenticator for the PoR. The security of our proposed scheme can be proved in the standard model, assuming the hash function is collision resilient and the computational Diffie–Hellman assumption holds. The scheme also supports data modification, data insertion and data deletion. Furthermore, our technique can also be regarded as a novel paradigm by combining the homomorphic signature and authenticated data structure (with certain properties) to construct the homomorphic linear authenticator for the PoR protocols.

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Notes

  1. \(\sigma _{i,2}\) is also stored by the CSS in \(\sigma \).

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Acknowledgements

The authors would like to thank Xue Liang, Zhao Yi, Zhou Yanwei and Lai Qiqi for their valuable comments. This work is supported by the National Key R&D Program of China (2017YFB080 2000), the National Natural Science Foundation of China (61772326, 61572303), NSFC Research Fund for International Young Scientists (61750110528), National Cryptography Development Fund during the 13th Five-year Plan Period (MMJJ20170216), the Foundation of State Key Laboratory of Information Security (2017-MS-03) and the Fundamental Research Funds for the Central Universities (GK201603092, GK201702004, GK201603084). It is also supported by Fund of Key Laboratory of Modern Teaching Technology, Ministry of Education, P.R.China (2015kfkt3).

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Authors and Affiliations

  1. School of Computer Science, Shaanxi Normal University, Xi’an, Shaanxi, 710119, China

    Tao Wang, Bo Yang, Yong Yu & Guoyong Qiu

  2. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China

    Tao Wang, Bo Yang & Yong Yu

  3. Key Laboratory of Modern Teaching Technology, Ministry of Education, Xi’an, Shaanxi, 710016, China

    Tao Wang

  4. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610054, China

    Hongyu Liu

  5. School of Computer Science and Technology, Wuhan University of Technology, Wuhan, Hubei, 430070, China

    Zhe Xia

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  1. Tao Wang
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Correspondence to Bo Yang.

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Wang, T., Yang, B., Liu, H. et al. An alternative approach to public cloud data auditing supporting data dynamics. Soft Comput 23, 4939–4953 (2019). https://doi.org/10.1007/s00500-018-3155-4

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