Neural networks (NNs) have become one of the most important tools for artificial
intelligence. Well-designed and trained NNs can perform inference (eg, make decisions or …

Secure multi-party computation (MPC) allows a set of parties to jointly compute a function on
their private inputs, and reveals nothing but the output of the function. In the last decade …

Succinct non-interactive arguments of knowledge (SNARKs) enable non-interactive efficient
verification of NP computations and admit short proofs. However, all current SNARK …

Threshold ECDSA receives interest lately due to its widespread adoption in blockchain
applications. A common building block of all leading constructions involves a secure …

Secure multiparty computation enables a set of parties to securely carry out a joint
computation on their private inputs without revealing anything but the output. A particularly …

Recently, Cramer et al.(CRYPTO 2018) presented a protocol, SPDZ2k, for actively secure
multiparty computation for dishonest majority in the pre-processing model over the ring Z …

In this work we present a novel actively secure multiparty computation protocol in the
dishonest majority setting, where the computation domain is a ring of the type Z 2 k. Instead …

A threshold public key encryption protocol is a public key system where the private key is
distributed among n different servers. It offers high security since no single server is …

An important characteristic of recent MPC protocols is an input-independent setup phase in
which most computations are offloaded, which greatly reduces the execution overhead of …

Secure multiparty computation (MPC) allows a set of mutually distrustful parties to compute a
public function on their private inputs without revealing anything beyond the output of the …