Privacy Lab is an application and utility created to help firms explore how privacy-enhancing technologies (PETs) can be incorporated into digital advertising workflows and how doing so may impact their advertising operations.
The notebook directory contains a Jupyter notebook with interactive examples that illustrate how selected PETs can be used to protect users' PII within a common digital advertising use case: measurement and attribution for digital advertising campaigns. The example workflows are informed by the IAB Tech Lab Attribution Data Matching Protocol (ADMaP) specification and incorporate Universal CAPI v1. The included workflow variants are enumerated below.
- Privacy-preserving aggregation of conversion data using k-anonymity
- Privacy-preserving aggregation of conversion data using differential privacy (DP)
- Privacy-preserving filtered aggregation of conversion data using homomorphic encryption