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 …

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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. It offers two tremendous advantages: “encryption in use” in addition to the already existing “encryption at rest” and “encryption in transit”, and enabling different parties to collaborate and gain insights from their aggregate data, without sharing their data with …

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