Privacy is a very active subject of research and also of debate in the political circles. In order to make good decisions about privacy, we need measurement systems for privacy. Most of the traditional measures such as k-anonymity lack expressiveness in many cases. We present a privacy measuring framework, which can be used to measure the value of privacy to an individual and also to evaluate the efficacy of privacy enhancing technologies. Our method is centered on a subject, whose privacy can be measured through the amount and value of information learned about the subject by some observers. This gives rise to interesting probabilistic models for the value of privacy and measures for privacy enhancing technologies.
Kimmo Halunen, Anni Karinsalo (VTT): Measuring the value of privacy and the efficacy of PETs
Presented at ECSA ’17 Proceedings of the 11th European Conference on Software Architecture, 11-15.Sep. 2017, Canterbury.