The purpose of Secure Multi-Party Computation is to enable protocol participants to compute a public function of their private inputs while keeping their inputs secret, without resorting to any trusted third party. However, opening the public output of such computations inevitably reveals some information about the private inputs. We propose a measure generalising both Rényi entropy and g-entro...

based on a meta-theoretical analysis of voting, the present paper is an attempt to present a theoretical model encompassing all the possible aspects of voting in an election action system, proposing four sub-systems of voting as follows: economic voting, political voting, cultural voting and moral voting. having distinguished among these sub-systems, the writer describes the constitutive elemen...

Trust in the New Economy by Avner Ben-Ner and Louis Putterman June 2002 Introduction What do trust and the economy have to do with each other? In a world of perfect and symmetric information, where all related economic actions are simultaneous and occur in one place, the economy runs in the familiar fashion of the perfectly competitive market. In such a world, trust among economic actors is not...

English In 2013, the Portable Circuit Format (PCF) project was started to improve the way circuits for secure computation can efficiently be built, stored and evaluated. Secure computation is a growing field of cryptography, especially in the last decade and allows two or more parties to jointly evaluate a common function over their inputs without the need to disclose any information but the fi...

-We present sTrack, a system that can track objects across distributed cameras without revealing any visual information to peering cameras except whether an object was seen by both parties. To achieve this challenging privacy goal, we build on recent advances in secure two-party computation and multi-camera object tracking. Starting from two distance-metric learning techniques that are foundati...

1.1. Secure Two-Party Computation. In essence, secure multiparty computation is the solution to the problem how to compute on private inputs from several parties when we do not trust other parties and we don’t have a central authority who can get inputs, perform computations and give outputs to those that need them. Here we will talk about secure twoparty computation, where Alice, holding xa an...

In information sharing networks, having a privacy preserving index (or PPI) is critically important for providing efficient search on access controlled content across distributed providers while preserving privacy. An understudied problem for PPI techniques is how to provide controllable privacy preservation, given the innate difference of privacy of the different content and providers. In this...