Privacy toolkit for data science collaboration

Daniel Huynh
Members Public

Rust: How We Built a Privacy Framework for Data Science

We could have built our privacy framework BastionLab in any language - Python, for example, which is data science’s beloved. But we chose Rust because of its efficiency and security features. Here are the reasons why we loved doing so, but also some challenges we encountered along the way.

Daniel Huynh
Members Public

Data Science: The Short Guide to Privacy Technologies

If you’re wondering what the benefits and weaknesses of differential privacy, confidential computing, federated learning, etc are, and how they can be combined to improve artificial intelligence and data privacy, you’ve come to the right place.

Daniel Huynh
Members Public

Introducing BastionLab - A Simple Privacy Framework for Data Science Collaboration

BastionLab is a simple privacy framework for data science collaboration. It lets data owners protect the privacy of their datasets and enforces that only privacy-friendly operations are allowed on the data and anonymized outputs are shown to the data scientist.

Daniel Huynh
Members Public

Our Roadmap to Build a Simple Privacy Toolkit for Data Science Collaboration

One year and a half later, Mithril Security’s roadmap has transformed significantly, but our initial goal stayed the same: democratizing privacy in data science.