Privacy As A Service: Publishing Data And Models

The main obstacle to the development of sustainable and productive ecosystems leveraging data is the unavailability of robust, reliable and convenient privacy management tools and services. We propose to demonstrate our Privacy-as-a-Service system and Liancheng, the Cloud system that hosts it. We consider not only the publication of data but also that of models created by parametric and non-parametric statistical machine learning algorithms. We illustrate the construction and execution of privacy preserving workflows using real-world datasets.