Efficient Multiparty Protocols Using Generalized Parseval's Identity and the Theta Algebra

08/21/2022
by   Giorgio Sonnino, et al.
0

We propose a protocol able to show publicly addition and multiplication on secretly shared values. To this aim we developed a protocol based on the use of masks and on the FMPC (Fourier Multi-Party Computation). FMPC is a novel multiparty computation protocol of arithmetic circuits based on secret-sharing, capable to compute addition and multiplication of secrets with no communication. We achieve this task by introducing the first generalisation of Parseval's identity for Fourier series applicable to an arbitrary number of inputs and a new algebra referred to as the "Theta-algebra". FMPC operates in a setting where users wish to compute a function over some secret inputs by submitting the computation to a set of nodes, without revealing them those inputs. FMPC offloads most of the computational complexity to the end users, and includes an online phase that mainly consists of each node locally evaluating specific functions. FMPC paves the way for a new kind of multiparty computation protocols; making it possible to compute addition and multiplication of secrets stepping away from circuit garbling and the traditional algebra introduced by Donald Beaver in 1991. Our protocol is capable to compute addition and multiplication with no communication and its simplicity provides efficiency and ease of implementation.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/05/2019

FMPC: Secure Multiparty Computation from Fourier Series and Parseval's Identity

FMPC is a novel multiparty computation protocol of arithmetic circuits b...
research
10/16/2020

Barrington Plays Cards: The Complexity of Card-based Protocols

In this paper we study the computational complexity of functions that ha...
research
01/10/2018

Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications

We present Chameleon, a novel hybrid (mixed-protocol) framework for secu...
research
06/08/2020

ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing

We propose ARIANN, a low-interaction framework to perform private traini...
research
10/09/2019

Secret key agreement from correlated data, with no prior information

A fundamental question that has been studied in cryptography and in info...
research
10/05/2019

Secure Montgomery Multiplication and Repeated Squares for Modular Exponentiation

The BMR16 circuit garbling scheme introduces gadgets that allow for ciph...

Please sign up or login with your details

Forgot password? Click here to reset