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dc.contributor.advisorNeagu, Daniel
dc.contributor.advisorRidley, Mick J.
dc.contributor.authorAlim, Sophia*
dc.date.accessioned2013-03-05T18:01:27Z
dc.date.available2013-03-05T18:01:27Z
dc.date.issued2013-03-05
dc.identifier.urihttp://hdl.handle.net/10454/5507
dc.description.abstractThe increase in online social network (OSN) usage has led to personal details known as attributes being readily displayed in OSN profiles. This can lead to the profile owners being vulnerable to privacy and social engineering attacks which include identity theft, stalking and re identification by linking. Due to a need to address privacy in OSNs, this thesis presents a framework to quantify the vulnerability of a user¿s OSN profile. Vulnerability is defined as the likelihood that the personal details displayed on an OSN profile will spread due to the actions of the profile owner and their friends in regards to information disclosure. The vulnerability measure consists of three components. The individual vulnerability is calculated by allocating weights to profile attribute values disclosed and neighbourhood features which may contribute towards the personal vulnerability of the profile user. The relative vulnerability is the collective vulnerability of the profiles¿ friends. The absolute vulnerability is the overall profile vulnerability which considers the individual and relative vulnerabilities. The first part of the framework details a data retrieval approach to extract MySpace profile data to test the vulnerability algorithm using real cases. The profile structure presented significant extraction problems because of the dynamic nature of the OSN. Issues of the usability of a standard dataset including ethical concerns are discussed. Application of the vulnerability measure on extracted data emphasised how so called ¿private profiles¿ are not immune to vulnerability issues. This is because some profile details can still be displayed on private profiles. The second part of the framework presents the normalisation of the measure, in the context of a formal approach which includes the development of axioms and validation of the measure but with a larger dataset of profiles. The axioms highlight that changes in the presented list of profile attributes, and the attributes¿ weights in making the profile vulnerable, affect the individual vulnerability of a profile. iii Validation of the measure showed that vulnerability involving OSN profiles does occur and this provides a good basis for other researchers to build on the measure further. The novelty of this vulnerability measure is that it takes into account not just the attributes presented on each individual profile but features of the profiles¿ neighbourhood.en_US
dc.language.isoenen_US
dc.rights<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.eng
dc.subjectPersonal information disclosureen_US
dc.subjectData retrievalen_US
dc.subjectVulnerabilityen_US
dc.subjectMeasurementen_US
dc.subjectPrivacy and OSNs.en_US
dc.subjectPersonal details in OSNs.en_US
dc.subjectOnline social networks (OSN)en_US
dc.subjectVulnerability algorithmen_US
dc.subjectIdentity theften_US
dc.titleVulnerability in online social network profiles. A Framework for Measuring Consequences of Information Disclosure in Online Social Networks.en_US
dc.type.qualificationleveldoctoralen_US
dc.publisher.institutionUniversity of Bradfordeng
dc.publisher.departmentDepartment of Computingen_US
dc.typeThesiseng
dc.type.qualificationnamePhDen_US
dc.date.awarded2011
refterms.dateFOA2018-07-19T09:26:39Z


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