Enabling Efficient Batch Updating Verification for Multi-versioned Data in Cloud Storage

QI Yining; TANG Xin; HUANG Yongfeng

doi:10.1049/cje.2018.02.007

Volume 28 Issue 2

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QI Yining, TANG Xin, HUANG Yongfeng, “Enabling Efficient Batch Updating Verification for Multi-versioned Data in Cloud Storage,” Chinese Journal of Electronics, vol. 28, no. 2, pp. 377-385, 2019, doi: 10.1049/cje.2018.02.007

Citation:

QI Yining, TANG Xin, HUANG Yongfeng, “Enabling Efficient Batch Updating Verification for Multi-versioned Data in Cloud Storage,” Chinese Journal of Electronics, vol. 28, no. 2, pp. 377-385, 2019, doi: 10.1049/cje.2018.02.007

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Enabling Efficient Batch Updating Verification for Multi-versioned Data in Cloud Storage

doi: 10.1049/cje.2018.02.007

1.
Department of Electronic Engineering, Tsinghua University, Beijing 100084, China;
2.
Tsinghua National Laboratory for Information Science and Technology, Beijing 100084, China

Funds: This work is supported by the National Key Research and Development Program of China (No.2016YFB0800402), the National Natural Science Foundation of China (No.U1405254, No.U1536207).

Received Date: 2017-06-19
Rev Recd Date: 2017-07-14
Publish Date: 2019-03-10

Abstract

Abstract

Existing dynamic data possession verification schemes not only suffer from low efficiency of rebalancing its Merkle Hash tree (MHT) when executing data updating, but also lack effective mechanism to verify multi-version files. Aiming at these problems, this paper propose a new data structure called Rank-based multi-version Merkle AVL tree (RBMV-MAT) to achieve efficient batch updating verification for multi-version data. RBMV-MAT uses a special lock and relaxed balance to decrease the frequency of rebalacing operations. The experimental results show that our efficient scheme has better efficiency than those of existing methods.
- Cloud storage,
- Data integrity,
- Provable data possession (PDP),
- Data dynamics,
- Cloud computing

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References(17)

References

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