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Cluster Computing

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21-12-2017

Privacy protection and integrity verification of aggregate queries in cloud computing

Authors: Jun Hong, Tao Wen, Quan Guo, Zhengwang Ye, Ying Yin

Published in: Cluster Computing | Special Issue 3/2019

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Abstract

Outsourcing data to the cloud becomes a trend for the users to reduce database management and maintenance cost. However, storing data on the cloud brings many security problems. Data privacy and query authentication are two critical issues to be resolved. Specially, they are important to aggregate queries of cloud data. The data owner must keep the sensitive data hidden and only the aggregate result is revealed to the clients and cloud service provider. Furthermore, the client can ensure that the aggregate results are correct and complete. In this paper, we adopt multi-party computation to realize privacy-preserving aggregate computation in which at least t cloud servers can jointly calculate the aggregate results without gaining any knowledge of sensitive data. In addition, we introduce an authenticated structure, called PAAT, to provide query authentication for aggregate result. The experimental results show that our scheme is feasible and has good performance in practice.

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Title: Privacy protection and integrity verification of aggregate queries in cloud computing
Authors: Jun Hong
Tao Wen
Quan Guo
Zhengwang Ye
Ying Yin
Publication date: 21-12-2017
Publisher: Springer US
Published in: Cluster Computing / Issue Special Issue 3/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-017-1521-0

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