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Valuating Privacy with Option Pricing Theory
Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Computer Science.
2010 (English)In: Economics of Information Security and Privacy / [ed] Tyler Moore, David Pym, and Christos Ioannidis, New York: Springer , 2010, p. 187-193Chapter in book (Refereed)
Abstract

One of the key challenges in the information society is responsible handling of personal data. An often-cited reason why people fail to make rational decisions regarding their own informational privacy is the high uncertainty about future consequences of information disclosures today. This chapter builds an analogy to financial options and draws on principles of option pricing to account for this uncertainty in the valuation of privacy. For this purpose, the development of a data subject's personal attributes over time and the development of the attribute distribution in the population are modelled as two stochastic processes, which fit into the Binomial Option Pricing Model (BOPM). Possible applications of such valuation methods to guide decision support in future privacy-enhancing technologies (PETs) are sketched

Place, publisher, year, edition, pages
New York: Springer , 2010. p. 187-193
Keywords [en]
privacy, metrics, option pricing theory
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-10132ISBN: 9781441969668 (print)OAI: oai:DiVA.org:kau-10132DiVA, id: diva2:493653
Available from: 2012-02-08 Created: 2012-02-08 Last updated: 2018-01-12Bibliographically approved
In thesis
1. Inter-temporal Privacy Metrics
Open this publication in new window or tab >>Inter-temporal Privacy Metrics
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Informational privacy of individuals has significantly gained importance after information technology has become widely deployed. Data, once digitalised, can be copied, distributed, and long-term stored at negligible costs. This has dramatic consequences for individuals that leave traces in the form of personal data whenever they interact with information technology, for instance, computers and phones; or even when information technology is recording the personal data of aware or unaware individuals. The right of individuals for informational privacy, in particular to control the flow and use of their personal data, is easily undermined by those controlling the information technology.

The objective of this thesis is to study the measurement of informational privacy with a particular focus on scenarios where an individual discloses personal data to a second party which uses this data for re-identifying the individual within a set of other individuals. We contribute with privacy metrics for several instances of this scenario in the publications included in this thesis, most notably one which adds a time dimension to the scenario for modelling the effects of the time passed between data disclosure and usage. The result is a new framework for inter-temporal privacy metrics.

Place, publisher, year, edition, pages
Karlstad: Karlstad University Press, 2014. p. 20
Series
Karlstad University Studies, ISSN 1403-8099 ; 2014:63
Keywords
privacy, unlinkability, metrics, uncertainty, valuation process, domain-specific language, anonymous communication
National Category
Computer Systems Communication Systems Probability Theory and Statistics
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-33972 (URN)978-91-7063-603-5 (ISBN)
Public defence
2014-12-16, Karlstad University, 21A342 (Eva Erikssonsalen), Universitetsgatan 2, 651 87 Karlstad, 08:15 (English)
Opponent
Supervisors
Available from: 2014-11-25 Created: 2014-10-03 Last updated: 2014-11-25Bibliographically approved

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