Abstract
The cloud storage auditing constructions derived from the primitives of homomorphic linear authenticator and polynomial-based authentication tag outperform other types of constructions in terms of the efficiency in verifier’s side. However, the batch auditing overheads regarding the storage and the computation in known constructions can be further reduced. And these constructions are improper for the standard batch auditing model. In this paper, we propose an efficient cloud storage auditing scheme supporting the batch auditing in standard model. To this end, the only nonce in the existing constructions is replaced with multiple nonces that are corresponding to each involved data owner. And the extended Euclidean algorithm is employed to generate the aggregated proof for batch auditing. In the proposed scheme, the overheads regarding storage and computation are both reduced to be as approximately large as the number of the involved data owners. The security analysis and the performance evaluation show that the proposed scheme is secure and efficient as expected.
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Acknowledgments
This work is supported by National Natural Science Foundation of China under Grant (No. 61772311) and China Scholarship Council (No. 201906220077).
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Yang, H., Su, Y., Qin, J., Ma, J., Wang, H. (2020). An Efficient Public Batch Auditing Scheme for Data Integrity in Standard Model. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12486. Springer, Cham. https://doi.org/10.1007/978-3-030-62223-7_51
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DOI: https://doi.org/10.1007/978-3-030-62223-7_51
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