Adaptively Secure Distributed PRFs from$$\mathsf {LWE}$$

Abstract

In distributed pseudorandom functions (DPRFs), a PRF secret key SK is secret shared among N servers so that each server can locally compute a partial evaluation of the PRF on some input X. A combiner that collects t partial evaluations can then reconstruct the evaluation F(SK, X) of the PRF under the initial secret key. So far, all non-interactive constructions in the standard model are based on lattice assumptions. One caveat is that they are only known to be secure in the static corruption setting, where the adversary chooses the servers to corrupt at the very beginning of the game, before any evaluation query. In this work, we construct the first fully non-interactive adaptively secure DPRF in the standard model. Our construction is proved secure under the assumption against adversaries that may adaptively decide which servers they want to corrupt. We also extend our construction in order to achieve robustness against malicious adversaries.