Trust and Security in Numbers
In plain English
AI plain-English summaryMulti-Party Computation (MPC) lets multiple organisations jointly compute answers from their combined data without any of them ever seeing each other’s raw information. For decades, MPC was a theoretical curiosity; now it is becoming practically realisable, and this fellowship will push it from fundamental mathematics through to working prototypes. The core problem is that today’s computing infrastructure forces a choice: share data openly (risking privacy) or keep it siloed (missing out on insights). MPC breaks that trade-off. The research covers the entire pipeline—from the underlying cryptographic protocols and systems engineering to programming tools and real-world demonstrators guided by an industrial advisory board. If successful, MPC could transform how hospitals collaborate on patient diagnostics without exposing records, how supply chains verify provenance without revealing proprietary data, and how energy grids balance loads across competing utilities without leaking commercial information. It also enables entirely new business models: parties that currently refuse to share data resources could do so without compromising privacy or security. This is fundamental science with a clear engineering path, not an immediate consumer product, but the protocols it produces could quietly underpin the trust architecture of future digital infrastructure.
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