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Privacy-Preserving Data Processing with Flexible Access Control

delete2020-03-01
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OA
AI
W
Wenxiu Ding
Z
Zheng Yan *
R
Robert H. Deng
DOI:10.1109/TDSC.2017.2786247delete
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摘要

摘要

En 中文
Cloud computing provides an efficient and convenient platform for cloud users to store, process and control their data. Cloud overcomes the bottlenecks of resource-constrained user devices and greatly releases their storage and computing burdens. However, due to the lack of full trust in cloud service providers, the cloud users generally prefer to outsource their sensitive data in an encrypted form, which, however, seriously complicates data processing, analysis, as well as access control. Homomorphic encryption (HE) as a single key system cannot flexibly control data sharing and access after encrypted data processing. How to realize various computations over encrypted data in an efficient way and at the same time flexibly control the access to data processing results has been an important challenging issue. In this paper, we propose a privacy-preserving data processing scheme with flexible access control. With the cooperation of a data service provider (DSP) and a computation party (CP), our scheme, based on Paillier's partial homomorphic encryption (PHE), realizes seven basic operations, i.e., Addition, Subtraction, Multiplication, Sign Acquisition, Absolute, Comparison, and Equality Test, over outsourced encrypted data. In addition, our scheme, based on the homomorphism of attribute-based encryption (ABE), is also designed to support flexible access control over processing results of encrypted data. We further prove the security of our scheme and demonstrate its efficiency and advantages through simulations and comparisons with existing work.
Keyword:
Cloud computing
Access control
Encryption
Data processing
Process control
Computational efficiency
Homomorphic encryption
privacy preservation
data sharing
attribute-based encryption
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期刊

IEEE Transactions on Dependable and Secure Computing 封面图
IEEE Transactions on Dependable and Secure Computing
IF:
7.5
论文数:
2.6K
被引数:
9.6K

机构

S
Singapore Management University
学者数:
1.5K
论文数: 2.5K
被引数: 3.5K
X
Xidian University
学者数:
2.4W
论文数: 1.9W
被引数: 9.7K
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