Federated learning (FL) is an increasingly popular approach for machine learning (ML) in
cases where the training dataset is highly distributed. Clients perform local training on their …

Efficient zero-knowledge (ZK) proofs for arbitrary boolean or arithmetic circuits have recently
attracted much attention. Existing solutions suffer from either significant prover overhead (ie …

Correlated oblivious transfer (COT) is a crucial building block for secure multi-party
computation (MPC) and can be generated efficiently via OT extension. Recent works based …

Zero-knowledge (ZK) proofs with an optimal memory footprint have attracted a lot of
attention, because such protocols can easily prove very large computation with a small …

We put forth new protocols for oblivious transfer extension and vector OLE, called Silver, for
SILent Vole and oblivious transfER. Silver offers extremely high performances: generating …

We consider the problem of securely generating useful instances of two-party correlations,
such as many independent copies of a random oblivious transfer (OT) correlation, using a …

Many recent private set intersection (PSI) protocols encode input sets as polynomials. We
consider the more general notion of an oblivious key-value store (OKVS), which is a data …

Secure multi-party computation (MPC) is an essential tool for privacy-preserving machine
learning (ML). However, secure training of large-scale ML models currently requires a …

Zero knowledge proofs are an important building block in many cryptographic applications.
Unfortunately, when the proof statements become very large, existing zero-knowledge proof …

This work introduces novel techniques to improve the translation between arithmetic and
binary data types in secure multi-party computation. We introduce a new approach to …