The project addresses the challenge of automated generation of scalable privacy-preserving mechanisms in IoT, cloud, and edge computing systems. The project designs SecQL, a query language for data-intensive applications, whose runtime environment automatically generates and deploys sub-computations over nodes of the above systems to optimize performance while protecting the processed data from unauthorized access. The formally defined SecQL makes privacy-preserving mechanisms accessible also for non-security experts.
Professor Dr. Eric Bodden and Professor Dr. Mira Mezini were the principal investigators of subproject E1.