Quantifying privacy: challenges, pitfalls, and ways forward
Many privacy metrics have been proposed in the last two decades to measure how much privacy users would enjoy if different privacy protections were built into modern technologies.
In this talk, I will explore what makes it difficult to measure privacy and analyze whether existing privacy metrics are good at measuring privacy accurately and consistently (not all of them are). I will then show how metrics suites – weighted combinations of different privacy metrics – can make privacy measurement stronger and more consistent.
Finally, I will discuss how measuring user privacy on the web is different from measuring the privacy gain offered by privacy protections. As an example, I will show the research methods and metrics that can be used to measure how much privacy is promised to users in privacy policies.
Prof. Isabel Wagner
Associate Professor in Computer Science (Cybersecurity)
De Montfort University, UK
Isabel Wagner is an Associate Professor in Computer Science with De Montfort University. Her research interests are in privacy and transparency, particularly metrics to quantify the effectiveness of privacy protections, privacy-enhancing technologies in smart cities, and web measurement to create transparency for corporate surveillance systems. Her new book “Auditing Corporate Surveillance Systems: Research Methods for Greater Transparency” has been published by Cambridge University Press in 2022. She is a senior member of ACM and IEEE.