PLASMA: Private, Lightweight Aggregated Statistics against Malicious Adversaries

Dimitris Mouris; Pratik Sarkar; Nektarios Georgios Tsoutsos

Paper 2023/080

PLASMA: Private, Lightweight Aggregated Statistics against Malicious Adversaries

Dimitris Mouris

, University of Delaware

Pratik Sarkar

, Boston University

Nektarios Georgios Tsoutsos

, University of Delaware

Abstract

Private heavy-hitters is a data-collection task where multiple clients possess private bit strings, and data-collection servers aim to identify the most popular strings without learning anything about the clients' inputs. In this work, we introduce PLASMA: a private analytics framework in the three-server setting that protects the privacy of honest clients and the correctness of the protocol against a coalition of malicious clients and a malicious server. Our core primitives are a verifiable incremental distributed point function (VIDPF) and a batched consistency check, which are of independent interest. Our VIDPF introduces new methods to validate client inputs based on hashing. Meanwhile, our batched consistency check uses Merkle trees to validate multiple client sessions together in a batch. This drastically reduces server communication across multiple client sessions, resulting in significantly less communication compared to related works. Finally, we compare PLASMA with the recent works of Asharov et al. (CCS'22) and Poplar (S&P'21) and compare in terms of monetary cost for different input sizes.

Note: The PLASMA GitHub repository is available here: https://github.com/TrustworthyComputing/plasma

Metadata

Available format(s): PDF
Category: Cryptographic protocols
Publication info: Published elsewhere. PoPETs 2024, Issue 3
Keywords: Function secret sharing private histograms private heavy hitters secure multiparty computation
Contact author(s): jimouris @ udel edu
pratik93 @ bu edu
tsoutsos @ udel edu
History: 2024-04-18: last of 3 revisions; 2023-01-23: received; See all versions
Short URL: https://ia.cr/2023/080
License: CC BY

BibTeX

@misc{cryptoeprint:2023/080,
      author = {Dimitris Mouris and Pratik Sarkar and Nektarios Georgios Tsoutsos},
      title = {PLASMA: Private, Lightweight Aggregated Statistics against Malicious Adversaries},
      howpublished = {Cryptology ePrint Archive, Paper 2023/080},
      year = {2023},
      note = {\url{https://eprint.iacr.org/2023/080}},
      url = {https://eprint.iacr.org/2023/080}
}