Google is extending differential privacy capabilities to the Python language, with an open source tool, called PipelineDP, for creating pipelines that aggregate data containing personal information in a way that preserves the privacy of individuals. The tool allows data engineers to visualize and tune parameters used to produce differentially private information.
PipelineDP, developed in partnership with OpenMined and accessible from the project website, is still in an experimental stage. With differential privacy, useful insights and services can be provided without revealing any information about individuals. PipelineDP follows the 2019 launch of an open source version of Google’s foundational differential privacy library, which works with the C++, Go, and Java languages.
