The Privacy-Utility Trade-off in the Topics API

The ongoing deprecation of third-party cookies by web browser vendors has sparked the proposal of alternative methods to support more privacy-preserving personalized advertising on web browsers and applications. The Topics API is being proposed by Google to provide third-parties with "coarse-grained advertising topics that the page visitor might currently be interested in". In this paper, we analyze the re-identification risks for individual Internet users and the utility provided to advertising companies by the Topics API, i.e. learning the most popular topics and distinguishing between real and random topics. We provide theoretical results dependent only on the API parameters that can be readily applied to evaluate the privacy and utility implications of future API updates, including novel general upper-bounds that account for adversaries with access to unknown, arbitrary side information, the value of the differential privacy parameter $ε$, and experimental results on real-world data that validate our theoretical model.

Christian Pietsch 🍑 (@[email protected])

#Firefox 128 is here. With it comes a new section in the privacy and security settings called "Website Advertising Preferences" containing a ticked box labeled "Allow websites to perform privacy-preserving ad measurement". The help text linked there sounds promising: https://support.mozilla.org/en-US/kb/privacy-preserving-attribution #Mozilla to provide a surveillance-free alternative to #tracking? Technical explainer: https://github.com/mozilla/explainers/tree/main/ppa-experiment What do #privacy experts think? #ppa #dap #privateAttribution #privacyPreservingAttribution

Pluralistic: 22 Apr 2021 – Pluralistic: Daily links from Cory Doctorow