Study on Privacy Risk Measurement Model of Cloud Computing

Author(s): Zifei Ma, Rong Jiang*, Ruiyin Li, Tong Li, Juan Yang, Qiujin Zhang.

Journal Name: Recent Patents on Computer Science

Volume 10 , Issue 4 , 2017

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Graphical Abstract:


Background: Problems of cloud user privacy leaks have already hindered the further development of cloud computing, as described in various patents. Therefore, the comprehensive analysis and measurement of cloud computing privacy risks factors is an effective way to control and identify risks. However, the researches about this issue have not yet been discovered, so the relevant issues have been focused in this paper.

Methods: This paper combines Analytic Hierarchy Process(AHP) with Information Entropy theory to identify and measure the privacy security risks of cloud computing.

Results: This paper constructs a privacy risk attribute model of cloud computing with 20 privacy risk factors, based on the model, a cloud computing privacy risk measurement model has been designed.

Conclusion: In order to effectively identify the defects and weakness on privacy protection, this paper can calculate the value and level of privacy risk factors of the attribute model by measuring model. The measurement results can provide a reference for cloud service providers to protect the privacy of users. Then the correctness of the model is verified by relevant simulation experiments.

Keywords: Cloud computing, privacy risks, risk measurement, information entropy, Analytic Hierarchy Process(AHP), privacy protection.

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Article Details

Year: 2017
Page: [315 - 324]
Pages: 10
DOI: 10.2174/2213275911666180216153940
Price: $58

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