Paper 2024/930

Information-Theoretic Single-Server PIR in the Shuffle Model

Yuval Ishai, Technion – Israel Institute of Technology
Mahimna Kelkar, Cornell University
Daniel Lee, Massachusetts Institute of Technology
Yiping Ma, University of Pennsylvania
Abstract

We revisit the problem of private information retrieval (PIR) in the shuffle model, where queries can be made anonymously by multiple clients. We present the first single-server PIR protocol in this model that has sublinear per-client communication and information-theoretic security. Moreover, following one-time preprocessing on the server side, our protocol only requires sublinear per-client computation. Concretely, for every $\gamma>0$, the protocol has $O(n^{\gamma})$ communication and computation costs per (stateless) client, with $1/\text{poly}(n)$ statistical security, assuming that a size-$n$ database is simultaneously accessed by $\text{poly}(n)$ clients. This should be contrasted with the recent breakthrough result of Lin, Mook, and Wichs (STOC 2023) on doubly efficient PIR in the standard model, which is (inherently) limited to computational security.

Metadata
Available format(s)
PDF
Category
Cryptographic protocols
Publication info
Published elsewhere. Major revision. ITC 2024
Keywords
shuffle modelprivate information retrieval
Contact author(s)
yuvali @ cs technion ac il
mahimna @ cs cornell edu
lee_d @ mit edu
yipingma @ seas upenn edu
History
2024-06-12: approved
2024-06-10: received
See all versions
Short URL
https://ia.cr/2024/930
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2024/930,
      author = {Yuval Ishai and Mahimna Kelkar and Daniel Lee and Yiping Ma},
      title = {Information-Theoretic Single-Server {PIR} in the Shuffle Model},
      howpublished = {Cryptology ePrint Archive, Paper 2024/930},
      year = {2024},
      note = {\url{https://eprint.iacr.org/2024/930}},
      url = {https://eprint.iacr.org/2024/930}
}
Note: In order to protect the privacy of readers, eprint.iacr.org does not use cookies or embedded third party content.