1970-01-01

(2025-12) Fully Distributed Multi-Point Functions for PCGs and Beyond

[[Amit Agarwal]]
[[Srinivasan Raghuraman]]
[[Peter Rindal]]

2025-12-19

Abstract

We introduce new {Distributed Multi-Point Function} (DMPF) constructions that make multi-point sharing as practical as the classic single-point (DPF) case. Our main construction, {Reverse Cuckoo}, replaces the ``theoretical'' cuckoo insertions approach to DMPFs with a MPC-friendly linear solver that circumvents the concrete inefficiencies. Combined with our new sparse DPF construction, we obtain the first fully distributed and efficient DMPF key generation that avoids trusted dealers and integrates cleanly with standard two-party MPC.

Applied to pseudorandom correlation generators (PCGs), our DMPFs remove the dominant “sum of $t$ DPFs'' bottleneck. In Ring-LPN and Stationary-LPN pipelines (Crypto 2020, 2025), this translates to {an order of magnitude more Beaver triples per second} with {an order of magnitude less communication} compared to the status quo by Keller et al (Eurocrypt 2018). The gains persist across fields and rings ( $\mathbb{F}_{p^k}$ , $\mathbb{Z}_{2^k}$ for $k\geq 1$ ) and are complementary to existing PCG frameworks: our constructions drop in as a black-box replacement for their sparse multi-point steps, accelerating {all} PCGs that rely on such encodings.

We provide a complete protocol suite (deduplication, hashing, linear solver, sparse DPF instantiation) with a semi-honest security proof via a straight-line simulator that reveals only hash descriptors and aborts with negligible (cuckoo-style) probability. A prototype implementation validates the asymptotics with strong concrete performance improvements.