Prochlo: Strong Privacy for Analytics in the Crowd
This addresses privacy concerns for users in analytics and monitoring applications, representing a novel approach rather than an incremental improvement.
The paper tackles the problem of large-scale software activity monitoring while protecting user privacy, introducing the Encode, Shuffle, Analyze (ESA) architecture and its Prochlo implementation to achieve high utility in such systems.
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)