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Distilling Mobile Privacy Requirements from Qualitative Data

Keerthi, Thomas (2014). Distilling Mobile Privacy Requirements from Qualitative Data. PhD thesis The Open University.

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Abstract

As mobile computing applications have become commonplace, it is increasingly important for them to address end-users' privacy requirements. Mobile privacy requirements depend on a number of contextual socio-cultural factors to which mobility adds another level of contextual variation. However, traditional requirements elicitation methods do not sufficiently account for contextual factors and therefore cannot be used effectively to represent and analyse the privacy requirements of mobile end users. On the other hand, methods that investigate contextual factors tend to produce data which can be difficult to use for requirements modelling. To address this problem, we have developed a Distillation approach that employs a problem analysis model to extract and refine privacy requirements for mobile applications from raw data gathered through empirical studies involving real users. Our aim was to enable the extraction of mobile privacy requirements that account for relevant contextual factors while contributing to the software design and implementation process. A key feature of the distillation approach is a problem structuring framework called privacy facets (PriF). The facets in the PriF framework support the identification of privacy requirements from different contextual perspectives namely - actors, information, information-flows and places. The PriF framework also aids in uncovering privacy determinants and threats that a system must take into account in order to support the end-user's privacy. In this work, we first show the working of distillation using qualitative data taken from an empirical study which involved social-networking practices of mobile users. As a means of validating distillation, another distinctly separate qualitative dataset from a location-tracking study is used, in both cases, the empirical studies relate to privacy issues faced by real users observed in their mobile environment.

Item Type: Thesis (PhD)
Copyright Holders: 2014 Thomas Keerthi
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 40121
Depositing User: Keerthi Thomas
Date Deposited: 03 Jun 2014 12:49
Last Modified: 05 Oct 2016 07:54
URI: http://oro.open.ac.uk/id/eprint/40121
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