Private Polynomial Computation for Noncolluding Coded Databases

Document Type

Conference Proceeding

Publication Date

7-1-2019

Abstract

We consider private polynomial computation (PPC) over noncolluding coded databases. In such a setting a user wishes to compute a multivariate polynomial of degree at most g over f variables (or messages) stored in multiple databases while revealing no information about the desired polynomial to the databases. We construct two novel PPC schemes, where the first is a generalization of our previous work in private linear computation for coded databases. In this scheme we consider Reed-Solomon coded databases with Lagrange encoding, which leverages ideas from recently proposed star-product private information retrieval and Lagrange coded computation. The second scheme considers the special case of coded databases with systematic Lagrange encoding. Both schemes yield improved rates compared to the best known schemes from the literature for a small number of messages, while in the asymptotic case the rates match.

Identifier

85073144355 (Scopus)

ISBN

[9781538692912]

Publication Title

IEEE International Symposium on Information Theory Proceedings

External Full Text Location

https://doi.org/10.1109/ISIT.2019.8849825

ISSN

21578095

First Page

1677

Last Page

1681

Volume

2019-July

Grant

1526547

Fund Ref

National Science Foundation

This document is currently not available here.

Share

COinS