Share your thoughts, 1 month free Claude Pro on usSee more
WorkDL logo mark

Prochlo: Strong Privacy for Analytics in the Crowd

About

The large-scale monitoring of computer users' software activities has become commonplace, e.g., for application telemetry, error reporting, or demographic profiling. This paper describes a principled systems architecture---Encode, Shuffle, Analyze (ESA)---for performing such monitoring with high utility while also protecting user privacy. The ESA design, and its Prochlo implementation, are informed by our practical experiences with an existing, large deployment of privacy-preserving software monitoring. (cont.; see the paper)

Andrea Bittau, \'Ulfar Erlingsson, Petros Maniatis, Ilya Mironov, Ananth Raghunathan, David Lie, Mitch Rudominer, Usharsee Kode, Julien Tinnes, Bernhard Seefeld• 2017

Related benchmarks

TaskDatasetResultRank
ForecastingComStock (val)
RMSE0.386
18
Load forecastingLondon Household Electricity (val)
RMSE0.418
18
Load forecastingPecan Street (val)
RMSE0.377
18
Sample Inference AttackCIFAR-10 shadow dataset (test)
Original SIA Success Rate45
4
Privacy Leakage EvaluationCIFAR-10
Cosine AUC0.36
3
Showing 5 of 5 rows

Other info

Follow for update