@inproceedings{dc8e09a032db4333819d3beedc0f15fd,
title = "Computationally Secure Aggregation and Private Information Retrieval in the Shuffle Model",
abstract = "The shuffle model has recently emerged as a popular setting for differential privacy, where clients can communicate with a central server using anonymous channels or an intermediate message shuffler. This model was also explored in the context of cryptographic tasks such as secure aggregation and private information retrieval (PIR). However, this study was almost entirely restricted to the stringent notion of information-theoretic security. In this work, we study computationally secure aggregation protocols and PIR in the shuffle model. Our starting point is the insight that the previous technique of shuffling additive shares can be improved in the computational setting. We show that this indeed holds under the standard learning parity with noise (LPN) assumption, but even better efficiency follows from plausible conjectures about the multi-disjoint syndrome decoding (MDSD) problem that we introduce and study in this work. We leverage the above towards improving the efficiency of secure aggregation and PIR in the shuffle model. For secure aggregation of long vectors, our protocols require 9×–25× less communication than the previous information-theoretic solutions. Our PIR protocols enjoy the simplicity and concrete efficiency benefits of multi-server PIR while only requiring a single server to store the database. Under the MDSD assumption, they improve over recent single-server PIR constructions by up to two orders of magnitude.",
keywords = "private information retrieval, secure aggregation, shuffle model, sparse LPN, syndrome decoding, variable-size records",
author = "Adri{\`a} Gasc{\'o}n and Yuval Ishai and Mahimna Kelkar and Baiyu Li and Yiping Ma and Mariana Raykova",
note = "Publisher Copyright: {\textcopyright} 2024 Copyright held by the owner/author(s).; 31st ACM SIGSAC Conference on Computer and Communications Security, CCS 2024 ; Conference date: 14-10-2024 Through 18-10-2024",
year = "2024",
month = dec,
day = "9",
doi = "https://doi.org/10.1145/3658644.3670391",
language = "الإنجليزيّة",
series = "CCS 2024 - Proceedings of the 2024 ACM SIGSAC Conference on Computer and Communications Security",
pages = "4122--4136",
booktitle = "CCS 2024 - Proceedings of the 2024 ACM SIGSAC Conference on Computer and Communications Security",
}