Anonymizing subsets of social networks

dc.contributor.authorGaertner, Jared Glen
dc.contributor.supervisorStege, Ulrike
dc.contributor.supervisorSrinivasan, Venkatesh
dc.date.accessioned2012-08-23T18:57:14Z
dc.date.available2012-08-23T18:57:14Z
dc.date.copyright2012en_US
dc.date.issued2012-08-23
dc.degree.departmentDepartment of Computer Science
dc.degree.levelMaster of Science M.Sc.en_US
dc.description.abstractIn recent years, concerns of privacy have become more prominent for social networks. Anonymizing a graph meaningfully is a challenging problem, as the original graph properties must be preserved as well as possible. We introduce a generalization of the degree anonymization problem posed by Liu and Terzi. In this problem, our goal is to anonymize a given subset of vertices in a graph while adding the fewest possible number of edges. We examine different approaches to solving the problem, one of which finds a degree-constrained subgraph to determine which edges to add within the given subset and another that uses a greedy approach that is not optimal, but is more efficient in space and time. The main contribution of this thesis is an efficient algorithm for this problem by exploring its connection with the degree-constrained subgraph problem. Our experimental results show that our algorithms perform very well on many instances of social network data.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.bibliographicCitationSean Chester, Jared Gaertner, Ulrike Stege, and S. Venkatesh. Anonymizing subsets of social networks with degree constrained subgraphs. In Proceedings of the International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE Computer Society, 2012.en_US
dc.identifier.urihttp://hdl.handle.net/1828/4157
dc.languageEnglisheng
dc.language.isoenen_US
dc.rights.tempAvailable to the World Wide Weben_US
dc.subjectprivacyen_US
dc.subjectsocial networken_US
dc.subjectdegree-constrained subgraphsen_US
dc.subjectk-degree anonymizationen_US
dc.subjectsubset graph anonymizationen_US
dc.titleAnonymizing subsets of social networksen_US
dc.typeThesisen_US

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