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    Vulnerability in online social network profiles. A Framework for Measuring Consequences of Information Disclosure in Online Social Networks.

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    VULNERABILITY IN ONLINE SOCIAL NETWORK PROFILES (Final_Submission).pdf (2.477Mb)
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    Publication date
    2013-03-05
    Author
    Alim, Sophia
    Supervisor
    Neagu, Daniel
    Ridley, Mick J.
    Keyword
    Personal information disclosure
    Data retrieval
    Vulnerability
    Measurement
    Privacy and OSNs.
    Personal details in OSNs.
    Online social networks (OSN)
    Vulnerability algorithm
    Identity theft
    Rights
    Creative Commons License
    The University of Bradford theses are licenced under a Creative Commons Licence.
    Institution
    University of Bradford
    Department
    Department of Computing
    Awarded
    2011
    
    Metadata
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    Abstract
    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. 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.
    URI
    http://hdl.handle.net/10454/5507
    Type
    Thesis
    Qualification name
    PhD
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    Theses

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