Secure multi-party computation (MPC) allows parties to perform computations on data while
keeping that data private. This capability has great potential for machine-learning …

This article provides a comprehensive and illustrative presentation of the young field of
encrypted control. In particular, we survey the evolution of encrypted controllers from their …

With the ever-increasing requirement of storage and computation resources, it is unrealistic
for local devices (with limited sources) to implement large-scale data processing. Therefore …

Secure computation enables mutually distrusting parties to jointly evaluate a function on
their private inputs without revealing anything but the function's output. Generic secure …

We put forward a new framework that makes it possible to re-write or compress the content
of any number of blocks in decentralized services exploiting the blockchain technology. As …

Secure multi-party computation (MPC) allows a group of mutually distrustful parties to
compute a joint function on their inputs without revealing any information beyond the result …

Abstract SPDZ (pronounced “Speedz”) is the nickname of the MPC protocol of Damgård et
al. from Crypto 2012. In this paper we both resolve a number of open problems with SPDZ; …

While traditional symmetric algorithms like AES and SHA-3 are optimized for efficient
hardware and software implementations, a range of emerging applications using advanced …

In this work we provide efficient distributed protocols for generating shares of random noise,
secure against malicious participants. The purpose of the noise generation is to create a …

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 …