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\(\varvec{\textit{KDVEM}}\): a \(k\)-degree anonymity with vertex and edge modification algorithm

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Abstract

Privacy is one of the most important issues in social social network data sharing. Structure anonymization is a effective method to protect user from being reidentfied through graph modifications. The data utility of the distorted graph structure after the anonymization is a really severe problem. Reducing the utility loss is a new measurement while k-anonymity as a criterion to guarantee privacy protection. The existing anonymization algorithms that use vertex’s degree modification usually introduce a large amount of distortion to the original social network graph. In this paper, we present a \(k\)-degree anonymity with vertex and edge modification algorithm which includes two phase: first, finding the optimal target degree of each vertex; second, deciding the candidates to increase the vertex degree and adding the edges between vertices to satisfy the requirement. The community structure factors of the social network and the path length between vertices are used to evaluated the anonymization methods. Experimental results on real world datasets show that the average relative performance between anonymized data and original data is the best with our approach.

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Acknowledgments

This work was supported in part by National Science Foundation of China (No. 61173143), Special Public Sector Research Program of China (Nos. GYHY201506080, GYHY201206030) China Postdoctoral Science Foundation (No. 2012M511303), and was also supported by PAPD. The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through Research Group No. RGP-264.

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Authors and Affiliations

  1. Jiangsu Engineering Centre of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Tinghuai Ma

  2. Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, Nanjing, 210044, China

    Tinghuai Ma

  3. School of Computer, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Yuliang Zhang & Jian Shen

  4. School of Economics and Management, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Jie Cao

  5. School of Public Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Meili Tang

  6. Computer Science Department, College of Computer and Information Science, King Saud University, Riyadh, 11362, Saudi Arabia

    Yuan Tian, Abdullah Al-Dhelaan & Mznah Al-Rodhaan

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  1. Tinghuai Ma
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  2. Yuliang Zhang
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  3. Jie Cao
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  4. Jian Shen
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  5. Meili Tang
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  6. Yuan Tian
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  7. Abdullah Al-Dhelaan
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  8. Mznah Al-Rodhaan
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Correspondence to Tinghuai Ma.

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Ma, T., Zhang, Y., Cao, J. et al. \(\varvec{\textit{KDVEM}}\): a \(k\)-degree anonymity with vertex and edge modification algorithm. Computing 97, 1165–1184 (2015). https://doi.org/10.1007/s00607-015-0453-x

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  • DOI: https://doi.org/10.1007/s00607-015-0453-x

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