@misc{anderson2021precio,
author = {Anderson, Erik and Chase, Melissa and Durak, Betül and Laine, Kim and Weng, Chenkai},
title = {Precio: Private Aggregate Measurement via Oblivious Shuffling},
year = {2021},
month = {November},
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.},
url = {http://approjects.co.za/?big=en-us/research/publication/aggregate-measurement-via-oblivious-shuffling/},
}