The 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.
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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.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/5507 |
| Date | January 2011 |
| Creators | Alim, Sophia |
| Contributors | Neagu, Daniel, Ridley, Mick J. |
| Publisher | University of Bradford, Department of Computing |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Thesis, doctoral, PhD |
| 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>. |
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