PropertyValue
?:abstract
  • We present a multi-language, cross-platform, open-source library for asymmetric private set intersection (PSI) and PSI-Cardinality (PSI-C). Our protocol combines traditional DDH-based PSI and PSI-C protocols with compression based on Bloom filters that helps reduce communication in the asymmetric setting. Currently, our library supports C++, C, Go, WebAssembly, JavaScript, Python, and Rust, and runs on both traditional hardware (x86) and browser targets. We further apply our library to two use cases: (i) a privacy-preserving contact tracing protocol that is compatible with existing approaches, but improves their privacy guarantees, and (ii) privacy-preserving machine learning on vertically partitioned data.
is ?:annotates of
?:arxiv_id
  • 2011.09350
?:creator
?:externalLink
?:license
  • arxiv
?:pdf_json_files
  • document_parses/pdf_json/4676d19e9c3dba577c605c2900a9b341b4a1005b.json
?:publication_isRelatedTo_Disease
?:sha_id
?:source
  • ArXiv
?:title
  • Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning
?:type
?:year
  • 2020-11-18

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