The goal of privacy metrics is to measure the degree of privacy enjoyed by users in a system and the amount of protection offered by privacy-enhancing technologies. In this way, privacy metrics contribute to improving user privacy in the digital world. The diversity and complexity of privacy metrics in the literature makes an informed choice of metrics challenging. As a result, redundant new metrics are proposed frequently, and privacy studies are often incomparable. In this survey we alleviate these problems by structuring the landscape of privacy metrics. For this we explain and discuss a selection of over eighty privacy metrics and introduce a categorization based on the aspect of privacy they measure, their required inputs, and the type of data that needs protection. In addition, we present a method on how to choose privacy metrics based on eight questions that help identify the right privacy metrics for a given scenario, and highlight topics where additional work on privacy metrics is needed. Our survey spans multiple privacy domains and can be understood as a general framework for privacy measurement.
Privacy metrics, whose goal is to measure the degree of privacy enjoyed by users in a system and the amount of protection offered by privacy-enhancing technologies REF , have attracted the interest of several important studies.
Technical Privacy Metrics: a Systematic Survey
Isabel Wagner and David Eckhoff. 2018. Technical Privacy Metrics: a Systematic Survey. ACM Comput. Surv. 51, 3, Article 57 (June 2018)
Computer Science Mathematics