Title: Correlated Pseudorandomness from the Hardness
of the Quasi-Abelian Decoding Problem: the MPC
perspective.
Abstract: Secure multiparty computation relies on a
reliable source of correlated randomness to achieve
better efficiency. Recently, Boyle et al. explained how
correlated randomness can be generated by pseudorandom
correlation generators (PCGs). We construct PCGs for
random oblivious linear evaluation (OLE) correlation,
using a new assumption, the quasi-abelian syndrome
decoding problem (QA-SD). Furthermore, our PCG is also
said to be programmable and can be used to generate
multiparty correlated randomness to be used in silent
secure N -party protocols. Previous works constructed
very efficient (non-programmable) PCGs for correlations
such as random oblivious transfer but were less satisfying
in the case of the OLE. Using our new PCGs, we obtain the
first efficient n-party silent secure computation protocols
for computing general arithmetic circuit over F_q for any q>2.
I will explore how correlated randomness helps in multiparty
computation and explain the different tools we used to finally
conclude with the construction of our PCGs.
