Collaborative, Privacy-Preserving Data Aggregation at Scale

64 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Prio: Private, Robust, and Scalable Computation of Aggregate Statistics (2017, background): “, exact max), and some special-case MPC protocols [5, 29, 96] are practical today for certain applications.”
SplitX: high-performance private analytics (2013, methodology): “[5] uses a twoserver architecture, in which one server provides anonymity to participants and obliviously blinds keys, and the other server aggregates blinded keys’ values.”
Fast and Private Computation of Cardinality of Set Intersection and Union (2012, background): “, collaborative botnet detection [31], denial-ofservice identification [2], on-line gaming [7], intelligence-community systems [23], location sharing [32], just to cite a few.”
Secure Two-Party Computation is Practical (2009, methodology): “It was also used in a recent system for secure collaborative large-scale data aggregation for identifying denial-of-service attacks [34].”