An algorithm for κ-degree anonymity on large networks

Jordi Casas-Roma, Jordi Herrera-Joancomartí, Vicenç Torra

Research output: Contribution to journalArticleResearchpeer-review

44 Citations (Scopus)


In this paper, we consider the problem of anonymization on large networks. There are some anonymization methods for networks, but most of them can not be applied on large networks because of their complexity. We present an algorithm for κ-degree anonymity on large networks. Given a network G, we construct a κ-degree anonymous network, G̃, by the minimum number of edge modifications. We devise a simple and efficient algorithm for solving this problem on large networks. Our algorithm uses univariate micro-aggregation to anonymize the degree sequence, and then it modifies the graph structure to meet the κ-degree anonymous sequence. We apply our algorithm to a different large real datasets and demonstrate their efficiency and practical utility.

Original languageAmerican English
Pages (from-to)671-675
Number of pages5
JournalProceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013
Publication statusPublished - 2013


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