AD-MPC: Asynchronous Dynamic MPC with Guaranteed Output Delivery

MPC-as-a-Service (MPCaaS) systems enable clients to outsource privacy-preserving computations to distributed servers, offering flexibility by adapting and configuring MPC protocols to meet diverse security requirements. However, traditional MPC protocols rely on a fixed set of servers for the entire computation process, limiting scalability. Dynamic MPC (DMPC) addresses this limitation by permitting participants to join or leave during the computation. Nevertheless, existing DMPC protocols assume synchronous networks, which can lead to failures under unbounded network delays. In this paper, we present AD-MPC, the first asynchronous dynamic MPC protocol. Our protocol ensures guaranteed output delivery under optimal resilience ((n = 3t + 1)). To achieve this, we introduce two critical components: an asynchronous dynamic preprocessing protocol that facilitates the on-demand generation of Beaver triples for secure multiplication, and an asynchronous transfer protocol that maintains consistency during party hand-offs. These components collectively ensure computation correctness and transfer consistency across participants. We implement AD-MPC and evaluate its performance across up to 20 geographically distributed nodes. Experimental results demonstrate that the protocol not only offers strong security guarantees in dynamic and asynchronous network environments but also achieves performance comparable to state-of-the-art DMPC protocols.