Many applications in finance and healthcare need access to data from multiple
organizations. While these organizations can benefit from computing on their joint datasets …

Federated analytics is a way to answer queries over sensitive data that is spread across
multiple parties, without sharing the data or collecting it in a single place. Prior work has …

Recent years have witnessed significant advances in programming technology for multi-
party computation (MPC), bringing MPC closer to practice and wider applicability. Typical …

Secure Multi-Party Computation (MPC) is continuously becoming more and more practical.
Many optimizations have been introduced, making MPC protocols more suitable for solving …

Secure multi-party computation of Chebyshev distance represents a crucial method for
confidential distance measurement, holding significant theoretical and practical implications …

While secure multi-party computation (MPC) protects the privacy of inputs and intermediate
values of a computation, differential privacy (DP) ensures that the output itself does not …

Secure multi-party computation (SMPC) enables multiple parties to evaluate functions of
their private inputs, in a way such that none of the parties can learn anything about the other …

Abstract Multi-Party Computation (MPC) is a cryptographic technique that enables a number
of parties to perform useful computations while keeping their inputs private. The challenge is …

We introduce a new compiler for multi-party computation (MPC) which performs backend-
independent optimizations over the MPC Source intermediate representation and outputs …

Abstract Expressive cryptography, including Secure Multi-Party Computation (SMPC), Fully
Homomorphic Encryption (FHE), and policy-based encryption, has the potential to enable …