Graph k-Anonymity through k-Means and as Modular Decomposition

  • Klara Stokes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8208)


In this paper we discuss k-anonymous graphs in terms of modular decomposition and we present two algorithms for the k-anonym-ization of graphs with respect to neighborhoods. This is the strictest definition of k-anonymity for graphs. The first algorithm is an adaptation of the k-means algorithm to neighborhood clustering in graphs. The second algorithm is distributed of message passing type, and therefore enables user-privacy: the individuals behind the vertices can jointly protect their own privacy. Although these algorithms are not optimal in terms of information loss, they are a first example of algorithms that provide k-anonymization of graphs with respect to the strictest definition, and they are simple to implement.


k-anonymity graph modular decomposition message passing distributed algorithm k-means user-privacy 


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Klara Stokes
    • 1
  1. 1.Dept. of Computer and Information ScienceLinköping UniversityLinköpingSweden

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