UCLA

Secure multi-party computation (MPC) is one of the most important primitives in cryptography. Several directions to construct and improve MPC protocols have been studied over the past decades. The majority of existing MPC protocols rely on assumptions such as every party communicates with every other party or every party needs to know every other party and the computation algorithm well in advance. Such assumptions can be difficult to achieve in modern large scale networks. This thesis explores two distinct lines of work leading to new practical models in response to these scenarios.

First, we examine communication locality, the total number of other parties that each party communicates with in the protocol, as a new measure for an MPC protocol. Although progress has been made, the question of achieving low communication locality and round complexity at the same time for adaptive adversaries corrupting t < n/2 parties remains open. We show that by assuming a public-key infrastructure (PKI) and a symmetric-key infrastructure (SKI) the above question can be answered affirmatively, under standard assumptions. In particular, we describe a protocol with polylogarithmic communication locality and round complexity which tolerates up to t < n/2 adaptive corruptions. Our results are based on a new model of hidden random graphs obtained from the SKI, and using them to emulate a complete network in polylogarithmic rounds and polylogarithmic locality.

We then examine multi-key fully homomorphic encryption (MFHE) schemes, which allow computation on data encrypted under different public keys chosen independently of each other. One of the main problems left in MFHE has been on how to deal with malicious users without trusted setup assumptions. We show how this can be done through circuit privacy, which guarantees that even if both ciphertexts and public keys are not well-formed, no information is revealed regarding the computation, other than what follows from the output on some well-formed inputs. Generalizing the result for circuit-private FHE, we provide a framework for adding circuit privacy to existing MFHE schemes.

Finally, we incorporate the circuit privacy in a variant of server-assisted MPC, called on-the-fly MPC, where a server or a “cloud” performs an arbitrary dynamically chosen computation on a subset of data uploaded by multiple clients and encrypted under different keys on-the-fly. Circuit privacy allows the server to keep the algorithm used in the computation private even from a malicious adversary corrupting any number of clients. In particular, we construct a three-round on-the-fly MPC protocol with circuit privacy against malicious clients without the trusted setup.