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SDABS: A Secure Cloud Data Auditing Scheme Based on Blockchain and SGX

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Blockchain and Trustworthy Systems (BlockSys 2020)

Abstract

With the continuous growth of data resources, outsourcing data storage to cloud service providers is becoming the norm. Unfortunately, once data are stored on the cloud platform, they will be out of data owners’ control. Thus, it is critical to guarantee the integrity of the remote data. To solve this problem, researchers have proposed many data auditing schemes, which often employ a trusted role named Third Party Auditor (TPA) to verify the integrity. However, the TPA may not be reliable as expected. For example, it may collude with cloud service providers to hide the fact of data corruption for benefits. Blockchain has the characteristics of decentralization, non-tampering, and traceability, which provides a solution to trace the malicious behaviors of the TPA. Moreover, Intel SGX, as the popular trusted computing technology, can be used to protect the correctness of the auditing operations with a slight performance cost, which excellently serves as the of the blockchain-based solution. In this paper, we propose a secure auditing scheme based on the blockchain and Intel SGX technology, termed SDABS. The scheme follows the properties of storage correctness, data-preserving, accountability, and anti-collusion. The experiment results show that our scheme is efficient.

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Acknowledgements

This study is supported by Oxford-Hainan Blockchain Research Institute, the National Science Foundation of China (No. 61472074, U1708262) and the Fundamental Research Funds for the Central Universities (No. N172304023).

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Correspondence to Qinghao Wang .

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Lei, H., Bao, Z., Wang, Q., Zhang, Y., Shi, W. (2020). SDABS: A Secure Cloud Data Auditing Scheme Based on Blockchain and SGX. In: Zheng, Z., Dai, HN., Fu, X., Chen, B. (eds) Blockchain and Trustworthy Systems. BlockSys 2020. Communications in Computer and Information Science, vol 1267. Springer, Singapore. https://doi.org/10.1007/978-981-15-9213-3_21

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  • DOI: https://doi.org/10.1007/978-981-15-9213-3_21

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  • Online ISBN: 978-981-15-9213-3

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