Prochlo

2017/10/02 by Andrea Bittau, Úlfar Erlingsson, Petros Maniatis +8 · 284 citations
Computer Science · Social Sciences · #Advanced Malware Detection Techniques #Computer software #Key (lock) #Privacy, Security, and Data Protection #Privacy-Preserving Technologies in Data #Software #Software deployment #Software system #cs.CR

paper · pdf · doi:10.1145/3132747.3132769

published as Proceedings of the 26th Symposium on Operating Systems Principles (SOSP), pp. 441-459, 2017

arxiv created 2017/10/02 · openalex publication_date 2017/10/12 · openalex created_date 2017/10/20 · arxiv updated 2018/12/21 · openalex updated_date 2026/08/05

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.

Citations

• Calibrating Noise to Sensitivity in Private Data Analysis
• Privacy integrated queries
• Protecting respondents identities in microdata release
• How to share a secret
• The Algorithmic Foundations of Differential Privacy

Cited by

• Decomposition-Based Optimal Bounds for Privacy Amplification via Shuffling
• Augmented Shuffle Protocols for Accurate and Robust Frequency Estimation under Differential Privacy