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arXiv · 1710.00901

Prochlo: Strong Privacy for Analytics in the Crowd

Andrea Bittau·Úlfar Erlingsson·Petros Maniatis·Ilya Mironov·Ananth Raghunathan·David Lie·Mitch Rudominer·Usharsee Kode·Julien Tinnes·Bernhard Seefeld
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Abstract

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)

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Andrea Bittau, Úlfar Erlingsson, Petros Maniatis, Ilya Mironov, Ananth Raghunathan, David Lie, Mitch Rudominer, Usharsee Kode, Julien Tinnes, Bernhard Seefeld. 2017-10-02. Prochlo: Strong Privacy for Analytics in the Crowd. https://doi.org/10.1145/3132747.3132769

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