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Author: Admin | 2025-04-28
Aim is to accelerate FHE to usable levels.The implications of a usable FHE technology would be tremendous for fields such as AI. Today, the vast majority of AI training takes place in the cloud, but privacy concerns do not allow companies in several key applications (finance and healthcare, for example) to send data into the cloud. With future ASIC accelerators for FHE, medical research companies or fintech startups could upload encrypted data into the cloud, train AI models with it and download the results, decrypting the result only once it was safely back in-house. Data can also be pooled – such as medical data from different hospitals – each party retains their data privacy but the AI is able to learn from it anyway.Large wordsThe challenge for each of the research teams in the DPRIVE program is to develop a hardware and software stack to accelerate FHE computation so that it is comparable to similar unencrypted data operations. Darpa’s requirements for the hardware include flexibility, scalability and programmability.One of the key approaches the teams will take is exploration of large arithmetic word sizes (LAWS). Current CPU design is based on 64-bit words, but FHE requires much longer word lengths. The signal-to-noise ratio for encrypted data is directly related to word size; longer words mean less noise is accumulated each time an FHE calculation is processed. This means more calculations can be performed before the irreparable noise threshold is reached (beyond which data can no longer be recovered). Teams are expected to explore word sizes up to thousands of bits.Verification of LAWS circuits is particularly difficult, since the circuit state space becomes unmanageably large. Darpa’s tender document says that previous verification attempts on large word size multipliers timed out when the word size reached 256 bits. Cryptographic circuits have a high burden of proof for mathematical correctness, which necessitates full-circuit verification.Teams will also explore novel approaches to memory management, flexible data structures and programming models.Duality TechnologiesDuality Technologies has been awarded $14.5m by Darpa for DPRIVE. The company is a start-up that helps regulatory-bound companies (mostly in the financial and medical fields) to share homomorphically encrypted data. Duality already provides commercial platforms based on FHE, such as SecurePlus, its middleware platform which allows companies to encrypt data and then run analytics on the encrypted data, on companies’ own servers or in the cloud.Kurt Rohloff (Image: Duality Technologies)“[Hardware FHE acceleration] is an issue
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