Intel to Collaborate with Microsoft on DARPA Program

What’s New: Intel today announced that it has signed an agreement with Defense Advanced Research Projects Agency (DARPA) to perform in its Data Protection in Virtual Environments (DPRIVE) program. The program aims to develop an accelerator for fully homomorphic encryption (FHE). Microsoft is the key cloud ecosystem and homomorphic encryption partner leading the commercial adoption of the technology once developed by testing it in its cloud offerings, including Microsoft Azure and the Microsoft JEDI cloud, with the U.S. government. The multiyear program represents a cross-team effort across multiple Intel groups, including Intel Labs, the Design Engineering Group and the Data Platforms Group, to tackle “the final frontier” in data privacy, which is computing on fully encrypted data without access to decryption keys.

“Fully homomorphic encryption remains the holy grail in the quest to keep data secure while in use. Despite strong advances in trusted execution environments and other confidential computing technologies to protect data while at rest and in transit, data is unencrypted during computation, opening the possibility of potential attacks at this stage. This frequently inhibits our ability to fully share and extract the maximum value out of data. We are pleased to be chosen as a technology partner by DARPA and look forward to working with them as well as Microsoft to advance this next chapter in confidential computing and unlock the promise of fully homomorphic encryption for all.”
– Rosario Cammarota, principal engineer, Intel Labs, and principal investigator, DARPA DPRIVE program

Why It Matters: Protecting the confidentiality of critical information — whether personal data or corporate intellectual property — is of strategic importance to businesses. Today, many rely on a variety of data encryption methods to protect information while it is in transit, in use and at rest. However, these techniques require that data be decrypted for processing. It is during this decrypted state that data can become more vulnerable for misuse.

Fully homomorphic encryption enables users to compute on always-encrypted data, or cryptograms. The data never needs to be decrypted, reducing the potential for cyberthreats. FHE, when implemented at scale, would enable organizations to use techniques, such as machine learning, to extract full value from large datasets while protecting data confidentiality across the data’s life cycle. Customers across industries such as healthcare, insurance and finance would benefit from new usages made possible by being able to use and extract value from sensitive data to its fullest extent without risk of exposure.