DARPA Awards Duality Technologies Multimillion Dollar Contract to Accelerate Machine Learning on Encrypted Data
DPRIVE Hardware Acceleration Project Aims to Achieve Mass Market Adoption Readiness for Data-in-Use Protection
HOBOKEN, N.J. , Jan. 10, 2023 /PRNewswire/ -- Duality Technologies, the leader in privacy preserving data collaboration, today announced that the company was selected for Phase II of the DARPA Data Protection in Virtual Environments (DPRIVE) program. New capabilities for accelerated privacy-protected machine learning developing in the project will be integrated into Duality Technology's secure data collaboration platform, offering customers the most comprehensive ability to apply data science and machine learning on sensitive data in an expedient and collaborative way that further breaks down data silos that exist within and between organizations.
"Duality emerged as an unequivocal global leader in making privacy technology real and practical, at orders of magnitude faster than anyone else," said Prof. Kurt Rohloff, chief technical officer and co-founder of Duality. "We have assembled a renowned hardware and software acceleration team and we are continuing to achieve massive strides toward making what many people still believe is impossible - possible."
With support from DARPA in the DPRIVE program, the Duality TREBUCHET team continues on its trajectory to leverage the Duality powered OpenFHE (openfhe.org) library for Fully Homomorphic Encryption (FHE) computations that aim to significantly reduce the current computational burden and drastically speed up FHE calculations. This leading open source FHE software library revolutionizes computation on encrypted data - ensuring data security to address applications for the US Government, Department of Defense (DoD) and in commercial applications.
Duality was selected for Phase II of DPRIVE after success in a fiercely competitive Phase I round that included hardware accelerations teams from the biggest and most capable technology companies in this area. In Phase I, the Duality-led team designed a hardware accelerator for machine learning on data encrypted using FHE. The team's successful design work in Phase I justified their selection for Phase II and the multimillion dollar research and development contract to design and prototype encrypted computing acceleration hardware. A goal of the Duality-led TREBUCHET team is to make machine learning (ML) on FHE-protected ciphertext just as fast as ML on unencrypted data by design a hardware accelerator integrated with advanced FHE software such as OpenFHE.
"This Phase II award further validates the ground-breaking work we are spearheading and I am immensely proud of our team, technology and the privacy-preserving revolution we are leading," added Rohloff.
For more information on our partnership with DARPA, our technology, and the Duality team leading this effort, read our white paper and watch the interview with our team.
This research was, in part, funded by the U.S. Government. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government.
Duality is the leader in privacy enhanced secure data collaboration, empowering organizations worldwide to maximize the value of their data without compromising on privacy or regulatory compliance. Founded and led by world-renowned cryptographers and data scientists, Duality operationalizes privacy enhancing technologies (PETs) to accelerate data insights by enabling analysis and AI on encrypted data, while preserving data privacy, compliance and protecting valuable IP. A Gartner Cool Vendor, Duality was named a Tech Pioneer 2021 by the World Economic Forum (WEF) and listed on Fast Company's 2020 Most Innovative Companies and recently won the 2022 CB Insights' AI 100, the 2022 RegTech 100 Awards, and the AIFinTech100 2022 Awards.
For more information, visit dualitytech.com and follow us on LinkedIn and Twitter.
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SOURCE Duality Technologies, Inc.
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