Technical Program

Paper Detail

Paper Title Private Polynomial Computation for Noncolluding Coded Databases
Paper IdentifierWE2.R6.5
Authors Sarah A. Obead, New Jersey Institute of Technology, United States; Hsuan-Yin Lin, Eirik Rosnes, Simula UiB, Norway; Joerg Kliewer, New Jersey Institute of Technology, United States
Session Private Computation II
Location Sorbonne, Level 5
Session Time Wednesday, 10 July, 11:40 - 13:20
Presentation Time Wednesday, 10 July, 13:00 - 13:20
Manuscript  Click here to download the manuscript
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.