Welcome to the resource topic for 2024/009
Title:
Distributed Protocols for Oblivious Transfer and Polynomial Evaluation
Authors: Aviad Ben Arie, Tamir Tassa
Abstract:A secure multiparty computation (MPC) allows several parties to
compute a function over their inputs while keeping their inputs private. In its basic setting, the protocol involves only parties that hold
inputs. In distributed MPC, there are also external servers who perform
a distributed protocol that executes the needed computation, without
learning information on the inputs and outputs. Here we propose distributed protocols for several fundamental MPC functionalities. We
begin with a Distributed Scalar Product (DSP) protocol for computing
scalar products of private vectors. We build upon DSP in designing
various protocols for Oblivious Transfer (OT): k-out-of-N OT, Priced
OT, and Generalized OT. We also use DSP for Oblivious Polynomial
Evaluation (OPE) and Oblivious Multivariate Polynomial Evaluation
(OMPE). All those problems involve a sender and a receiver, both of
whom hold private vectors; the goal is to let the receiver learn the
scalar product of those two vectors. However, in each of these problems the receiver must submit a vector of a specified form. Hence, a
crucial ingredient in our protocols is a sub-protocol for validating that
the receiver’s vector complies with the relevant restrictions, without
learning anything else on that vector. Therefore, while previous studies presented distributed protocols for 1-out-of-N OT and OPE, our
protocols are the first ones that are secure against malicious receivers.
Our distributed protocols for the other OT variants and for OMPE
are the first ones that handle such problems. In addition, while previous art assumed semi-honest servers, we present protocols that are
secure even when some of the servers are malicious. Our protocols
offer information-theoretic security and they are very efficient.
ePrint: https://eprint.iacr.org/2024/009
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