At Opaque, we’re building upon the open source software our team had previously developed. During our early efforts in doing so, however, we didn’t consider the effect the separation of repos within the MC2 project might have as our codebase grew; after all, most complex systems benefit from modularity. However, as we began integrating these individual components into a single platform, the modularized codebase with multiple repositories (the polyrepo) created hurdles and complexities within our engineering workflow. We realized that something needed to change and began considering moving all of our code into a single encapsulating repo, a monorepo, that would almost paradoxically simplify our lives drastically.

Summary: In this engineering blog post, we discuss technical details surrounding Opaque Systems’ closed source version of Opaque SQL. This project extends Apache Spark SQL with a physical operator layer that runs inside hardware enclaves to protect confidential data in use. However, this latest iteration contains physical operators that are vectorized and are being performed …

Accelerating Encrypted Analytics on Confidential Data by 20x Read More »

We are excited to announce the initial release of the MC² Project, a collection of open source tools for computing and collaborating on confidential data. Developed at UC Berkeley’s RISELab, MC² (Multi-Party Collaboration and Coopetition) enables rich analytics and machine learning on encrypted data, ensuring that data remains concealed even when it’s being processed. The …

Secure collaborative analytics and ML using MC² Read More »

TL;DR: We are excited to present Opaque SQL, an open-source platform for securely running Spark SQL queries on encrypted data-in-use. Originally built by top systems and security researchers at UC Berkeley, the platform uses hardware enclaves to securely execute queries on private data in an untrusted environment. Opaque SQL partitions the codebase into trusted and …

How to Run Spark SQL on Encrypted Data Read More »