Measuring the value of privacy and the efficacy of PETs

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    Abstract

    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.
    Original languageEnglish
    Title of host publicationCompanion Proceedings - 11th European Conference on Software Architecture, ECSA 2017
    PublisherAssociation for Computing Machinery ACM
    Pages132-137
    Number of pages6
    VolumePart F130530
    ISBN (Electronic)9781450352178
    ISBN (Print)978-1-4503-5217-8
    DOIs
    Publication statusPublished - 11 Sep 2017
    MoE publication typeA4 Article in a conference publication
    Event11th European Conference on Software Architecture, ECSA 2017 - Canterbury, United Kingdom
    Duration: 11 Sep 201715 Sep 2017

    Conference

    Conference11th European Conference on Software Architecture, ECSA 2017
    Abbreviated titleECSA 2017
    CountryUnited Kingdom
    CityCanterbury
    Period11/09/1715/09/17

    Keywords

    • Measurement
    • Metric
    • Privacy
    • Probability
    • Value

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