Title

Cloud data integrity checking with an identity-based auditing mechanism from RSA

RIS ID

106201

Publication Details

Yu, Y., Xue, L., Au, M. Ho., Susilo, W., Ni, J., Zhang, Y., Vasilakos, A. V. & Shen, J. (2016). Cloud data integrity checking with an identity-based auditing mechanism from RSA. Future Generation Computer Systems: the international journal of grid computing: theory, methods and applications, 62 (September), 85-91.

Abstract

Cloud data auditing is extremely essential for securing cloud storage since it enables cloud users to verify the integrity of their outsourced data efficiently. The computation overheads on both the cloud server and the verifier can be significantly reduced by making use of data auditing because there is no necessity to retrieve the entire file but rather just use a spot checking technique. A number of cloud data auditing schemes have been proposed recently, but a majority of the proposals are based on Public Key Infrastructure (PKI). There are some drawbacks in these protocols: (1) It is mandatory to verify the validity of public key certificates before using any public key, which makes the verifier incur expensive computation cost. (2) Complex certificate management makes the whole protocol inefficient. To address the key management issues in cloud data auditing, in this paper, we propose ID-CDIC, an identity-based cloud data integrity checking protocol which can eliminate the complex certificate management in traditional cloud data integrity checking protocols. The proposed concrete construction from RSA signature can support variable-sized file blocks and public auditing. In addition, we provide a formal security model for ID-CDIC and prove the security of our construction under the RSA assumption with large public exponents in the random oracle model. We demonstrate the performance of our proposal by developing a prototype of the protocol. Implementation results show that the proposed ID-CDIC protocol is very practical and adoptable in real life.

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Link to publisher version (DOI)

http://dx.doi.org/10.1016/j.future.2016.02.003