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Taxonomy for Information Privacy Metrics
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. Royal Institute of Technology.
2011 (English)In: Journal of International Commercial Law and Technology, ISSN 1901-8401, Vol. 6, no 4, 194-206 p.Article in journal (Refereed) Published
Abstract [en]

A comprehensive privacy framework is essential for the progress of the information privacy field. Some practical implications of a comprehensive framework are laying foundation for building information privacy metrics and having fruitful discussions. Taxonomy is an essential step in building a framework. This research study attempts to build taxonomy for the information privacy domain based on empirical data. The classical grounded theory approach introduced by Glaser was applied and incidents reported by the International Association of Privacy Professionals (IAPP) are used for building the taxonomy. These incidents include privacy related current research works, data breaches, personal views, interviews, and technological innovations. TAMZAnalyzer, an open source qualitative data analysis tool, was used in coding, keeping memos, sorting, and creating categories. The taxonomy is presented in seven themes and several categories including legal, technical, and ethical aspects. The findings of this study helps practitioners understand and discuss the subjects and academia work toward building a comprehensive framework and metrics for the information privacy domain.

Place, publisher, year, edition, pages
2011. Vol. 6, no 4, 194-206 p.
National Category
Computer and Information Science
URN: urn:nbn:se:su:diva-89902OAI: diva2:621435
Available from: 2013-05-14 Created: 2013-05-14 Last updated: 2013-05-15Bibliographically approved
In thesis
1. Discovering Constructs and Dimensions for Information Privacy Metrics
Open this publication in new window or tab >>Discovering Constructs and Dimensions for Information Privacy Metrics
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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. 

Place, publisher, year, edition, pages
Kista: Department of Computer and Systems Sciences, tockholm Univeristy, 2013. 169 p.
Report Series / Department of Computer & Systems Sciences, ISSN 1101-8526 ; 13-003
Information privacy, Privacy metrics, Data protection, Personal information
National Category
Computer and Information Science
Research subject
Computer and Systems Sciences
urn:nbn:se:su:diva-89336 (URN)978-91-7447-637-8 (ISBN)
Public defence
2013-06-10, sal C, Forum 100, Isafjordsgatan 39, Kista, 13:00 (English)
Sida - Swedish International Development Cooperation Agency

At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 6: Accepted.

Available from: 2013-05-16 Created: 2013-04-22 Last updated: 2013-05-15Bibliographically approved

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