@inproceedings{0e5e7da568764a7791af4cbf1dec3b2c,
title = "Private Polynomial Computation for Noncolluding Coded Databases",
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.",
author = "Obead, {Sarah A.} and Lin, {Hsuan Yin} and Eirik Rosnes and Jorg Kliewer",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Symposium on Information Theory, ISIT 2019 ; Conference date: 07-07-2019 Through 12-07-2019",
year = "2019",
month = jul,
doi = "10.1109/ISIT.2019.8849825",
language = "English (US)",
series = "IEEE International Symposium on Information Theory - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1677--1681",
booktitle = "2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings",
address = "United States",
}