Fluid MPC: MPC with Dynamic Participants
Abstract: Existing approaches to secure multiparty computation (MPC) require all the participants to commit to the entire duration of the protocol. As interest in MPC continues to grow, it is inevitable that there will be a desire to use it to evaluate increasingly complex functionalities on massive datasets, resulting in computations spanning several hours or days.
Such scenarios call for a dynamic participation model for MPC where participants have the flexibility to go offline as needed and (re)join when they have available computational resources. Such a model would also democratize access to privacy-preserving computation by facilitating an “MPC-as-a-service” paradigm — the deployment of MPC in volunteer-operated networks that perform computation on behalf of clients.
In this talk, I will present a new MPC model called “fluid MPC”, where parties can dynamically join and leave the computation. The minimum commitment required from each participant is referred to as “fluidity”, measured in the number of rounds of communication that it must stay online. I will elaborate on the various modeling choices that one could potentially consider in the Fluid MPC setting. I will conclude the talk with a discussing constructions of information-theoretic fluid MPC protocols in the honest-majority setting that achieve “maximal fluidity”, meaning that a party can exit the computation after receiving and sending messages in one round.
Bio: Aarushi Goel is a post-doctoral researcher at NTT Research, working with Sanjam Garg. Previously, she received her Ph.D. from Johns Hopkins University, where she was advised by Abhishek Jain.