Fast identity anonymization on graphs

  • Xuesong Lu*
  • , Yi Song
  • , Stéphane Bressan
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

54 Scopus citations

Abstract

Liu and Terzi proposed the notion of k-degree anonymity to address the problem of identity anonymization in graphs. A graph is k-degree anonymous if and only if each of its vertices has the same degree as that of, at least, k-1 other vertices. The anonymization problem is to transform a non-k-degree anonymous graph into a k-degree anonymous graph by adding or deleting a minimum number of edges. Liu and Terzi proposed an algorithm that remains a reference for k-degree anonymization. The algorithm consists of two phases. The first phase anonymizes the degree sequence of the original graph. The second phase constructs a k-degree anonymous graph with the anonymized degree sequence by adding edges to the original graph. In this work, we propose a greedy algorithm that anonymizes the original graph by simultaneously adding edges to the original graph and anonymizing its degree sequence. We thereby avoid testing the realizability of the degree sequence, which is a time consuming operation. We empirically and comparatively evaluate our new algorithm. The experimental results show that our algorithm is indeed more efficient and more effective than the algorithm proposed by Liu and Terzi on large real graphs.

Original languageEnglish
Title of host publicationDatabase and Expert Systems Applications - 23rd International Conference, DEXA 2012, Proceedings
PublisherSpringer Verlag
Pages281-295
Number of pages15
EditionPART 1
ISBN (Print)9783642325991
DOIs
StatePublished - 2012
Externally publishedYes
Event23rd International Conference on Database and Expert Systems Applications, DEXA 2012 - Vienna, Austria
Duration: 3 Sep 20126 Sep 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7446 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Database and Expert Systems Applications, DEXA 2012
Country/TerritoryAustria
CityVienna
Period3/09/126/09/12

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