Today, we are on a collision course between two powerful but conflicting trends. The first represents the immense reliance on intelligent decision making to provide business value, something that is enhanced and more robust with more data. The result is a growing demand for usable, high quality data. The second represents the increased emphasis on …
Come Join the Most Innovative Team in Confidential Computing Read More »
This week, we and our co-founders Ion Stoica, Wenting Zheng, and Chester Leung are thrilled to announce that we closed our Series A funding bringing our total funding to $31.6 million. We are also excited to announce that Ion Stoica, Founder & Chairman of Databricks and co-founder of Opaque, will be formally joining our board …
Charting the Way to Realizing the Potential of Confidential AI Read More »
Founded by the pioneers of the MC2 open source project from UC Berkeley RiseLab, Opaque creates the first collaborative analytics and AI platform for confidential computing. BERKELEY, CA – June 28, 2022 – Opaque Systems, the pioneers of collaborative analytics and AI for confidential computing, today announced it has raised $22 million in Series A …
Enclave innovation protects data from attack and unauthorized access, but it also presents immense challenges and obstacles to performing analytics and machine learning within and across teams. The inability to securely share data or analyze data that is owned by multiple parties has resulted in organizations having to restrict data access, eliminate data sets or …
The Analytics and AI Challenge in Confidential Computing Read More »
Our last blog post explained the concept of secure enclaves. In this blog post, we will specifically focus on hardware enclaves and discuss just how secure they are. Introduction But first, a refresher on hardware enclaves for our new readers. Hardware enclaves provide an isolated environment for code and data within an untrusted machine, where …
How to Defend Against Side-Channel Attacks on SGX Read More »
Some of the biggest barriers to cloud adoption are concerns about security, data loss/ leakage, and the associated legal and regulatory concerns with storing and processing data off-premises1. Several cloud data breach incidents in recent years indicate that these concerns are warranted as a result of constant insider and outsider threats. The challenge with Infrastructure …
Protecting our private information from the prying eyes of other people, governments, and corporations is on many people’s minds. At the same time, our lack of control over our own data makes us wonder if privacy even matters in this day and age. In this article, I’ll argue that protecting our Personally Identifiable Information (PII) …
New techniques in analytics and machine learning offer the ability to process ever-increasing amounts of data, but access to such data has lagged far behind the technological advances in data processing. High-value data is often split across multiple organizations and access to it is encumbered by business competition and regulatory constraints. For example, banks wish …
Federated Learning vs. Secure Collaborative Learning Read More »
This is part 2 of a two part blog post on our migration to the polyrepo. If you haven’t yet read part 1 and want some more context, you can find it here. In part 1 of this blog post, we discussed how our original polyrepo led to complicated workflows which hindered engineering productivity, why …
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 …
