Precio: Private Aggregate Measurement via Oblivious Shuffling

F.  Betül Durak; Chenkai Weng; Erik Anderson; Kim Laine; Melissa Chase

Paper 2021/1490

Precio: Private Aggregate Measurement via Oblivious Shuffling

F. Betül Durak

Chenkai Weng, Northwestern University

Erik Anderson, Microsoft

Kim Laine, Microsoft

Melissa Chase, Microsoft

Abstract

We introduce Precio, a new secure aggregation method for computing layered histograms and sums over secret shared data in a client-server setting. Precio is motivated by ad conversion measurement scenarios, where online advertisers and ad networks want to measure the performance of ad campaigns without requiring privacy-invasive techniques, such as third-party cookies. Precio has linear (communication) complexity in the number of data points and guarantees differentially private outputs. We formally analyze its security and privacy and present a thorough performance evaluation. The protocol supports much larger domains than Prio. It supports much more flexible aggregates than the DPF-based solution and in some settings has up to four orders of magnitude better performance.

Metadata

Available format(s): PDF
Category: Cryptographic protocols
Publication info: Preprint.
Keywords: secure computing secure aggregation
Contact author(s): betuldurak @ microsoft com
ckweng @ u northwestern edu
erikan @ microsoft com
kim laine @ microsoft com
melissac @ microsoft com
History: 2023-08-15: last of 3 revisions; 2021-11-15: received; See all versions
Short URL: https://ia.cr/2021/1490
License: CC BY

BibTeX

@misc{cryptoeprint:2021/1490,
      author = {F.  Betül Durak and Chenkai Weng and Erik Anderson and Kim Laine and Melissa Chase},
      title = {Precio: Private Aggregate Measurement via Oblivious Shuffling},
      howpublished = {Cryptology ePrint Archive, Paper 2021/1490},
      year = {2021},
      note = {\url{https://eprint.iacr.org/2021/1490}},
      url = {https://eprint.iacr.org/2021/1490}
}