Paper 2024/705
Large-Scale MPC: Scaling Private Iris Code Uniqueness Checks to Millions of Users
Abstract
In this work we tackle privacy concerns in biometric verification systems that typically require server-side processing of sensitive data (e.g., fingerprints and Iris Codes). Concretely, we design a solution that allows us to query whether a given Iris Code is similar to one contained in a given database, while all queries and datasets are being protected using secure multiparty computation (MPC). Addressing the substantial performance demands of operational systems like World ID and aid distributions by the Red Cross, we propose new protocols to improve performance by more than three orders of magnitude compared to the recent state-of-the-art system Janus (S&P 24). Our final protocol can achieve a throughput of over 690 thousand Iris Code comparisons per second on a single CPU core, while protecting the privacy of both the query and database Iris Codes. Furthermore, using Nvidia NCCL we implement the whole protocol on GPUs while letting GPUs directly access the network interface. Thus we are able to avoid the costly data transfer between GPUs and CPUs, allowing us to achieve a throughput of 4.29 billion Iris Code comparisons per second in a 3-party MPC setting, where each party has access to 8 H100 GPUs. This GPU implementation achieves the performance requirements set by the Worldcoin foundation and will thus be used in their deployed World ID infrastructure.
Note: Rewriting to include protocol updates (Galois Shamir sharing) and implementation updates (full GPU acceleration).
Metadata
- Available format(s)
-
PDF
- Category
- Cryptographic protocols
- Publication info
- Preprint.
- Keywords
- MPCIris CodesuniquenessprivacyWorld IDGPU
- Contact author(s)
-
remco @ worldcoin org
bryan @ inversed tech
kales @ taceo io
philipp @ worldcoin org
walch @ taceo io - History
- 2024-10-17: revised
- 2024-05-07: received
- See all versions
- Short URL
- https://ia.cr/2024/705
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2024/705,
author = {Remco Bloemen and Bryan Gillespie and Daniel Kales and Philipp Sippl and Roman Walch},
title = {Large-Scale {MPC}: Scaling Private Iris Code Uniqueness Checks to Millions of Users},
howpublished = {Cryptology {ePrint} Archive, Paper 2024/705},
year = {2024},
url = {https://eprint.iacr.org/2024/705}
}