Privacy is a fundamental human right. During the last decades, in the information age, information privacy has become one of the most essential aspects of privacy. Information privacy is concerned with protecting personal information pertaining to individuals. Organizations, which frequently process the personal information, and individuals, who are the subjects of the information, have different needs, rights and obligations. Organizations need to utilize personal information as a basis to develop tailored services and products to their customers in order to gain advantage over their competitors. Individuals need assurance from the organizations that their personal information is not changed, disclosed, deleted or misused in any other way. Without this guarantee from the organizations, individuals will be more unwilling to share their personal information. Information privacy metrics is a set of parameters used for the quantitative assessment and benchmark of an organization’s measures to protect personal information. These metrics can be used by organizations to demonstrate, and by individuals to evaluate, the type and level of protection given to personal information. Currently, there are no systematically developed, established or widely used information privacy metrics. Hence, the purpose of this study is to establish a solid foundation for building information privacy metrics by discovering some of the most critical constructs and dimensions of these metrics. The research was conducted within the general research strategy of design science and by applying research methods such as data collection and analysis informed by grounded theory as well as surveys using interviews and questionnaires in Sweden and in Sri Lanka. The result is a conceptual model for information privacy metrics including its basic foundation; the constructs and dimensions of the metrics. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 6: Accepted.</p>
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-89336 |
Date | January 2013 |
Creators | Dayarathna, Rasika |
Publisher | Stockholms universitet, Institutionen för data- och systemvetenskap, Kista : Department of Computer and Systems Sciences, tockholm Univeristy |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Doctoral thesis, comprehensive summary, info:eu-repo/semantics/doctoralThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
Relation | Report Series / Department of Computer & Systems Sciences, 1101-8526 ; 13-003 |
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