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Our Migration to Monorepo – Part 1

Introduction Our team spent years at UC Berkeley actively building open source software to support our published research. The open source software, the MC2 Project, is a platform consisting of various libraries and packages that enable secure collaborative analytics and machine learning. While building the platform we created a repository (repo) for each paper; as …

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Why I’m Joining Opaque

After years of building and shipping products in various areas of the tech industry, I decided to join a company that set out to enable the widespread adoption of strong privacy measures and make a real impact in the world. With so much of our personal data now being stored and processed by any number …

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Accelerating Encrypted Analytics on Confidential Data by 20x

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 …

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Secure collaborative analytics and ML using MC²

Secure Collaborative Analytics and ML Using MC²

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 data in use remains …

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Run Spark SQL on Encrypted Data

How to Run Spark SQL Queries on Encrypted Data

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 untrusted sections to improve runtime …

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Secure computation: Homomorphic encryption or hardware enclaves

Secure Computation: Homomorphic Encryption or Hardware Enclaves?

Secure computation has become increasingly popular for protecting the privacy and integrity of data during computation. The reason is that it provides two tremendous advantages. The first advantage is that it offers “encryption in use” in addition to the already existing “encryption at rest” and “encryption in transit”. The “encryption in use” paradigm is important …

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Data Analytics Platform Opaque Systems Raises $9.5 Million Seed from Intel Capital and Race Capital to Unlock Encrypted Data with Machine Learning

Opaque Systems provides solutions that make it easier for enterprises to analyze confidential data through secure means, unlocking a $3 trillion market SAN FRANCISCO–(BUSINESS WIRE) — July 7, 2021: Opaque Systems, the secure data analytics platform company, today announced $9.5M in seed funding, led by Intel Capital with participation by Race Capital, The House Fund, …

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