Paper 2025/635

Towards Scalable YOSO MPC via Packed Secret-Sharing

Abstract

The YOSO (You Only Speak Once) model, introduced by Gentry et al. (CRYPTO 2021), helps to achieve strong security guarantees in cryptographic protocols for distributed settings, like blockchains, with large number of parties. YOSO protocols typically employ smaller anonymous committees to execute individual rounds of the protocol instead of having all parties execute the entire protocol. After completing their tasks, parties encrypt protocol messages for the next anonymous committee and erase their internal state before publishing ciphertexts, thereby enhancing security in dynamically changing environments. In this work, we consider the problem of secure multi-party computation (MPC), a fundamental problem in cryptography and distributed computing. We assume honest majority among the committee members, and work in the online-offline, i.e., preprocessing, setting. In this context, we present the first YOSO MPC protocol where efficiency---measured as communication complexity---improves as the number of parties increases. Specifically, for $$ and an adversary corrupting $$ out of $$ parties, our MPC protocol exhibits enhanced scalability as $$ increases, where the online phase communication becomes independent of $$. Prior YOSO MPC protocols considered $$ as large as $$, but a significant hurdle persisted in obtaining YOSO MPC with communication that does not scale linearly with the number of committee members, a challenge that is exagerbated when the committee size was large per YOSO's requirements. We show that, by considering a small ``gap'' of $$, the sizes of the committees are only marginally increased, while online communication is significantly reduced. Furthermore, we explicitly consider fail-stop adversaries, i.e., honest participants who may inadvertently fail due to reasons such as denial of service or software/hardware errors. In prior YOSO work, these adversaries were grouped with fully malicious parties. Adding explicit support for them allows us to achieve even better scalability.