  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 a million Iris Code comparisons
per second on a single CPU core, while protecting the privacy of both the query
and database Iris Codes. We additionally investigate GPU acceleration for some
building blocks of our protocol, which results in further speedups of over 38x
compared to the respective multi-threaded CPU implementation.
