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Mathematical Problems in Engineering
Volume 2017, Article ID 4785142, 11 pages
Research Article

Privacy Data Decomposition and Discretization Method for SaaS Services

1School of Computer Science & Technology and School of Software, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210003, China
2College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016, China
3Jiangsu High Tech. Research Key Laboratory for Wireless Sensor Networks, Nanjing, Jiangsu 210003, China
4Department of E-Commerce, Nanjing Audit University, Nanjing, Jiangsu 211815, China

Correspondence should be addressed to Changbo Ke; nc.ude.tpujn@ek.oborb

Received 17 April 2017; Accepted 28 May 2017; Published 9 July 2017

Academic Editor: Emilio Insfran

Copyright © 2017 Changbo Ke et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.