Research of Privacy-Preserving for Graph Mining of Government Affairs Office Automation Systems

Feng Qin Zhang; Liang Dong; Shui Ping Zhang; Xiao Qing Li; Gui Rong Chen

doi:10.4028/www.scientific.net/AMM.543-547.3004

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 543-547Research of Privacy-Preserving for Graph Mining of...

Research of Privacy-Preserving for Graph Mining of Government Affairs Office Automation Systems

Abstract:

Against the problems of privacy leakage from the graph of workflow structure of the government affair OA systems, the paper puts forwards a privacy preserving model which is effective in the protection of degrees and workflow amounts of the nodes in the government business workflow graph. For further implementation, it proposes a new unified anonymization algorithm oriented the actual nodes in the workflow graph based on the ides of social network anonymization and a new method of random weights disturbing to prevent the important nodes in the graph from being recognized by attackers and protect the information of workflow amount in the government and public institutions. At the end of this paper, the model has been verified by two experimentations that proves its feasibility and usability.

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Periodical:

Applied Mechanics and Materials (Volumes 543-547)

Pages:

3004-3008

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.543-547.3004

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Online since:

March 2014

Authors:

Feng Qin Zhang*, Liang Dong, Shui Ping Zhang, Xiao Qing Li, Gui Rong Chen

Keywords:

Government Affairs Office Automation, Graph Mining, Privacy Preserving, Workflow Graph

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* - Corresponding Author

References

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