Comparing Random-based and k-Anonymity-Based Algorithms for Graph Anonymization

Abstract

Recently, several anonymization algorithms have appeared for privacy preservation on graphs. Some of them are based on random- ization 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.