Privacy Data Decomposition and Discretization Method for SaaS Services

Changbo Ke, Zhiqiu Huang, Fu Xiao and Linyuan Liu

Mathematical Problems in Engineering, 2017, vol. 2017, 1-11

Abstract:

In cloud computing, user functional requirements are satisfied through service composition. However, due to the process of interaction and sharing among SaaS services, user privacy data tends to be illegally disclosed to the service participants. In this paper, we propose a privacy data decomposition and discretization method for SaaS services. First, according to logic between the data, we classify the privacy data into discrete privacy data and continuous privacy data. Next, in order to protect the user privacy information, continuous data chains are decomposed into discrete data chain, and discrete data chains are prevented from being synthesized into continuous data chains. Finally, we propose a protection framework for privacy data and demonstrate its correctness and feasibility with experiments.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:4785142

DOI: 10.1155/2017/4785142

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