Comparing random-based and k-anonymity-based algorithms for graph anonymization

Authors:
Jordi Casas-Roma;Jordi Herrera-Joancomartí;Vicenç Torra
Affiliations:
Department of Computer Engineering, Multimedia and Telecomunications (EIMT), Universitat Oberta de Catalunya (UOC), Barcelona, Spain;Department of Information and Communications Engineering (DEIC), Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain;Artificial Intelligence Research Institute (IIIA), Spanish National Research Council (CSIC), Bellaterra, Spain
Venue:
MDAI'12 Proceedings of the 9th international conference on Modeling Decisions for Artificial Intelligence
Year:
2012

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Abstract

Recently, several anonymization algorithms have appeared for privacy preservation on graphs. Some of them are based on randomization techniques and on k-anonymity concepts. We can use both of them to obtain an anonymized graph with a given k-anonymity value. In this paper we compare algorithms based on both techniques in order to obtain an anonymized graph with a desired k-anonymity value. We want to analyze the complexity of these methods to generate anonymized graphs and the quality of the resulting graphs.