Intel will collaborate with Microsoft in the creation of a homomorphic encryption for DARPA

 Intel announced today that it has managed to sign an agreement with the Defense Advanced Research Projects Agency (DARPA) of the United States to act in its Data Protection in Virtual Environments (DPRIVE) program. The program aims to develop an accelerator for fully homomorphic encryption (FHE).

Microsoft is the leading cloud and homomorphic encryption ecosystem partner leading commercial adoption of the technology once it is developed, testing it across its cloud offerings, including Microsoft Azure and the Microsoft JEDI cloud, with the United States government. The multi-year program represents a cross-cutting effort by various Intel groups, including Intel Labs, the Design Engineering Group, and the Data Platforms Group, to address the "last frontier" of data privacy. , which is computing on fully encrypted data without access to decryption keys.

"Fully homomorphic encryption remains the holy grail in the pursuit of data security during use. Despite great advances in trusted execution environments and other confidential computing technologies to protect data while at rest and in transit, the data is not encrypted during the calculation, which opens the possibility of possible attacks in this phase. This often inhibits our ability to share and extract the maximum value from the data ", said Rosario Cammarota, principal engineer of Intel Labs and Principal Investigator for DARPA's DPRIVE program.

"We are delighted to have been chosen as a technology partner by DARPA and look forward to working with them, as well as Microsoft, to advance this next chapter of confidential computing and unlock the promise of fully homomorphic encryption for all."

Fully homomorphic encryption allows users to calculate on always-encrypted data or cryptograms. Data never needs to be decrypted, reducing the potential for cyber threats. FHE, when implemented at scale, will enable organizations to use techniques, such as machine learning, to extract the full value of large data sets, while protecting the confidentiality of data throughout its life cycle. Clients in sectors such as healthcare, insurance and finance would benefit from possible new uses by being able to use and extract the value of sensitive data to its full extent without the risk of exposure.