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We present a multi-language, cross-platform, open-source library forasymmetric private set intersection (PSI) and PSI-Cardinality (PSI-C). Ourprotocol combines traditional DDH-based PSI and PSI-C protocols withcompression based on Bloom filters that helps reduce communication in theasymmetric setting. Currently, our library supports C++, C, Go, WebAssembly,JavaScript, Python, and Rust, and runs on both traditional hardware (x86) andbrowser targets. We further apply our library to two use cases: (i) aprivacy-preserving contact tracing protocol that is compatible with existingapproaches, but improves their privacy guarantees, and (ii) privacy-preservingmachine learning on vertically partitioned data.

Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning