Inter-temporal Privacy Metrics

Abstract: 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.