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Estimation of privacy risk through centrality metrics

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Estimation of privacy risk through centrality metrics

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dc.contributor.author Alemany-Bordera, José es_ES
dc.contributor.author Del Val Noguera, Elena es_ES
dc.contributor.author Alberola Oltra, Juan Miguel es_ES
dc.contributor.author García-Fornes, A es_ES
dc.date.accessioned 2019-07-03T20:02:51Z
dc.date.available 2019-07-03T20:02:51Z
dc.date.issued 2018 es_ES
dc.identifier.issn 0167-739X es_ES
dc.identifier.uri http://hdl.handle.net/10251/123142
dc.description.abstract [EN] Users are not often aware of privacy risks and disclose information in online social networks. They do not consider the audience that will have access to it or the risk that the information continues to spread and may reach an unexpected audience. Moreover, not all users have the same perception of risk. To overcome these issues, we propose a Privacy Risk Score (PRS) that: (1) estimates the reachability of an user¿s sharing action based on the distance between the user and the potential audience; (2) is described in levels to adjust to the risk perception of individuals; (3) does not require the explicit interaction of individuals since it considers information flows; and (4) can be approximated by centrality metrics for scenarios where there is no access to data about information flows. In this case, if there is access to the network structure, the results show that global metrics such as closeness have a high degree of correlation with PRS. Otherwise, local and social centrality metrics based on ego-networks provide a suitable approximation to PRS. The results in real social networks confirm that local and social centrality metrics based on degree perform well in estimating the privacy risk of users. es_ES
dc.description.sponsorship This work is partially supported by the Spanish Government project TIN2014-55206-R and FPI grant BES-2015-074498. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation info:eu-repo/grantAgreement/MINECO//TIN2014-55206-R/ES/PRIVACIDAD EN ENTORNOS SOCIALES EDUCATIVOS DURANTE LA INFANCIA Y LA ADOLESCENCIA/ es_ES
dc.relation info:eu-repo/grantAgreement/MINECO//BES-2015-074498/ES/BES-2015-074498/ es_ES
dc.relation info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-89156-R/ES/AGENTES INTELIGENTES PARA ASESORAR EN PRIVACIDAD EN REDES SOCIALES/ es_ES
dc.relation.ispartof Future Generation Computer Systems es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Privacy es_ES
dc.subject Social networks es_ES
dc.subject Information sharing es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Estimation of privacy risk through centrality metrics es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.future.2017.12.030 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Alemany-Bordera, J.; Del Val Noguera, E.; Alberola Oltra, JM.; García-Fornes, A. (2018). Estimation of privacy risk through centrality metrics. Future Generation Computer Systems. 82:63-76. https://doi.org/10.1016/j.future.2017.12.030 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.future.2017.12.030 es_ES
dc.description.upvformatpinicio 63 es_ES
dc.description.upvformatpfin 76 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 82 es_ES
dc.relation.pasarela S\349967 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Ministerio de Economía, Industria y Competitividad es_ES


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