Training AIs is essential to today’s tech sector, but handling the amount of data needed to do so is intrinsically dangerous. DARPA hopes to change that by tapping the encryption experts at Duality to ...

A technical paper titled “CraterLake: A Hardware Accelerator for Efficient Unbounded Computation on Encrypted Data” was published by researchers at MIT, IBM TJ Watson, SRI International, and ...

DAYTON, OH / ACCESS Newswire / December 3, 2025 / Niobium, a leading custom silicon provider for fully homomorphic encryption (FHE) platforms, today announced the close of a $23 million-plus ...

2024 JUN 03-- By a News Reporter-Staff News Editor at Insurance Daily News-- According to news reporting originating from Washington, D.C., by NewsRx journalists, a patent application by the inventors ...

A technical paper titled “BASALISC: Programmable Hardware Accelerator for BGV Fully Homomorphic Encryption” was published by researchers at COSIC KU Leuven, Galois Inc., and Niobium Microsystems.

Fabric Cryptography, a hardware startup by MIT and Stanford dropouts (and married couple) Michael Gao and Tina Ju, wants to make modern cryptographic techniques like zero-knowledge proof (which lets ...

The problem with encrypted data is that you must decrypt it in order to work with it. By doing so, it’s vulnerable to the very things you were trying to protect it from by encrypting it. There is a ...

Intel Innovation 2023: Attestation and Fully Homomorphic Encryption Coming to Intel Cloud Services Your email has been sent The attestation service is designed to allow data in confidential computing ...

Data theft and data loss is an endemic problem on the internet. According to the firm Risk Based Security (via TechRepublic), 2020 alone saw 3,932 publicly disclosed breaches with 37 billion records ...

AI and privacy needn’t be mutually exclusive. After a decade in the labs, homomorphic encryption (HE) is emerging as a top way to help protect data privacy in machine learning (ML) and cloud computing ...

What do you do when you need to perform computations on large data sets while preserving their confidentiality? In other words, you would like to gather analytics, for example, on user data, without ...