Optimal Single-Server Private Information Retrieval

Mingxun Zhou, Wei-Kai Lin, Yiannis Tselekounis, Elaine Shi

Abstract: We construct a single-server pre-processing Private Information Retrieval (PIR) scheme with optimal bandwidth and server computation (up to poly-logarithmic factors), assuming hardness of the Learning With Errors (LWE) problem. Our scheme achieves amortized $\widetilde{O}_{\lambda}(\sqrt{n})$ server and client computation and $\widetilde{O}_\lambda(1)$ bandwidth per query, completes in a single roundtrip, and requires $\widetilde{O}_\lambda(\sqrt{n})$ client storage. In particular, we achieve a significant reduction in bandwidth over the state-of-the-art scheme by Corrigan-Gibbs, Henzinger, and Kogan (Eurocrypt'22): their scheme requires as much as $\widetilde{O}_{\lambda}(\sqrt{n})$ bandwidth per query, with comparable computational and storage overhead as ours.

External IDs:dblp:journals/iacr/ZhouLTo22