Publication:
Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks

dc.contributor.authorPortela García-Miguel, Javier
dc.contributor.authorGarcía Villalba, Luis Javier
dc.contributor.authorSilva Trujillo, Alejandra Guadalupe
dc.contributor.authorSandoval Orozco, Ana Lucila
dc.contributor.authorKim, Tai-Hoon
dc.date.accessioned2023-06-18T00:05:06Z
dc.date.available2023-06-18T00:05:06Z
dc.date.issued2016-11-01
dc.description.abstractSocial network analysis aims to obtain relational data from social systems to identify leaders, roles, and communities in order to model profiles or predict a specific behavior in users’ network. Preserving anonymity in social networks is a subject of major concern. Anonymity can be compromised by disclosing senders’ or receivers’ identity, message content, or sender-receiver relationships. Under strongly incomplete information, a statistical disclosure attack is used to estimate the network and node characteristics such as centrality and clustering measures, degree distribution, and small-world-ness. A database of email networks in 29 university faculties is used to study the method. A research on the small-world-ness and Power law characteristics of these email networks is also developed, helping to understand the behavior of small email networks.
dc.description.departmentDepto. de Estadística y Ciencia de los Datos
dc.description.departmentDepto. de Ingeniería de Software e Inteligencia Artificial (ISIA)
dc.description.facultyFac. de Estudios Estadísticos
dc.description.facultyFac. de Informática
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/67732
dc.identifier.doi10.3390/s16111832
dc.identifier.issn1424-8220
dc.identifier.officialurlhttps://doi.org/10.3390/s16111832
dc.identifier.relatedurlhttps://www.mdpi.com/1424-8220/16/11/1832
dc.identifier.urihttps://hdl.handle.net/20.500.14352/19229
dc.issue.number11
dc.journal.titleSensors
dc.language.isoeng
dc.page.initial1832
dc.publisherMDPI
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/es/
dc.subject.keywordanonymity
dc.subject.keywordemail network
dc.subject.keywordgraph theory
dc.subject.keywordprivacy
dc.subject.keywordsocial network analysis
dc.subject.keywordsmall-world-ness
dc.subject.keywordstatistical disclosure attack
dc.subject.ucmRedes
dc.subject.ucmEstadística
dc.subject.unesco1209 Estadística
dc.titleEstimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks
dc.typejournal article
dc.volume.number16
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscovery44f935e8-9acf-4613-ab4d-e007edda7540
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