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In the recent years, privacy has gone from a niche idea to a mainstream concern. From protecting against surveillance to data theft, to enabling new healthcare or financial applications, the need to securely process data has never been so important.

Fortunately, many techniques are becoming practical, from Fully Homomorphic Encryption (FHE) to Secure Multiparty Computation (SMPC) to Federated Learning and Differential Privacy. All solve the same underlying problem to computing without being able to see the actual data, thus protecting privacy by design.

In this meetup, we will go deep into these techniques, from the theory (math heavy!) to the implementations (engineering heavy!) to the usecases (not as heavy!).

Send a message to hello@zama.ai if you'd like to present something

Upcoming events (1)

Efficient TFHE Bootstrapping in the Multiparty Setting

Link visible for attendees

Abstract

Many privacy preserving protocols are efficiently designed in a non-interactive way with practical implementation results thanks to recent improvements on FHE. However, some problems arise if we want to handle multiple users and also guarantee their input privacy.

If numerous users want to compute a common function keeping their input privacy, multi-key homomorphic encryption (MKHE) and multiparty homomorphic encryption (MPHE) (a.k.a. threshold-multikey FHE) are the best solutions for non-interactive protocols.

In this talk, we will explain the main differences between MKHE and MPHE, providing some example applications for both cases. We will then focus on how a MPHE scheme is constructed from an existing single-key FHE scheme. We will conclude by explaining a new technique (called homomorphic indicator) to construct an MPHE scheme from TFHE.

About the speaker

Sergi Rovira is a fourth-year PhD candidate in cryptography at Universitat Pompeu Fabra (UPF) under the supervision of Vanesa Daza (UPF) and Paz Morillo (UPC). Their research is focused on fully homomorphic encryption and lattice based post-quantum cryptography. Previously, they received a MSc in Advanced Mathematics and two BSc degrees, in Computer Science and in Mathematics from Universitat de Barcelona (UB).

Relevant paper / poster
📄 https://fhe.org/conferences/conference-2023/media/Poster_Multiparty_TFHE.pdf

Online event
🔗 https://zama-ai.zoom.us/j/81793675423

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Past events (28)

Hardware accelerator for FHEW

This event has passed

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