Neural Networks (NN) provide a powerful method for machine learning training and
inference. To effectively train, it is desirable for multiple parties to combine their data …

Cryptography is concerned with the conceptualization, definition, and construction of
computing systems that address security concerns. The design of cryptographic systems …

We present general definitions of security for multiparty cryptographic protocols, with focus
on the task of evaluating a probabilistic function of the parties' inputs. We show that, with …

In this paper the generality and wide applicability of Zero-knowledge proofs, a notion
introduced by Goldwasser, Micali, and Rackoff is demonstrated. These are probabilistic and …

More than ten years have elapsed since the rst completeness theorems for two-party and
multi-party fault-tolerant computation have been announced (by Yao and Goldreich, Micali …

Gathering and processing sensitive data is a difficult task. In fact, there is no common recipe
for building the necessary information systems. In this paper, we present a provably secure …

A fundamental problem in designing secure multi-party protocols is how to deal with
adaptive adversaries (ie, adversaries that may choose the corrupted parties during the …

Protecting Data Privacy in Private Information Retrieval Schemes Page 1 Protecting Data
Privacy in Private Information Retrieval Schemes Yael Gertner* Yuval Ishai t Eyal Kushilevitd …

This paper studies the problem of perfectly secure communication in general network in
which processors and communication lines may be faulty. Lower bounds are obtained on …

Neural Networks (NN) provide a powerful method for machine learning training and
inference. To effectively train, it is desirable for multiple parties to combine their data …