Deploying Secure Multi-Party Computation for Financial Data Analysis - (Short Paper)

Deploying secure multi-party computation for financial data analysis

In this paper we describe a secure system for jointly collecting and analyzing financial data for a consortium of ICT companies. To guarantee each participant’s privacy, we use secret sharing and secure multi-party computation (MPC) techniques. While MPC has been used to solve real-life problems beforehand, this is the first time where the actual MPC computation on real data was done over the i...

Deploying secure multiparty computation for joint data analysis — a case study

Mobile Commerce: Secure Multi-party Computation & Financial Cryptography

The basic objective of this work is to construct an efficient and secure mechanism for mobile commerce applying the concept of financial cryptography and secure multi-party computation. The mechanism (MCM) is defined by various types of elements: a group of agents or players, actions, a finite set of inputs of each agent, a finite set of outcomes as defined by output function, a set of objectiv...

Changing Neighbors k Secure Sum Protocol for Secure Multi Party Computation

Secure sum computation of private data inputs is an important component of Secure Multi-party Computation (SMC).In this paper we provide a protocol to compute the sum of individual data inputs with zero probability of data leakage. In our proposed protocol we break input of each party into number of segments and change the arrangement of the parties such that in each round of the computation th...

Privacy-Preserving Methods for Sharing Financial Risk Exposures

Unlike other industries in which intellectual property is patentable, the financial industry relies on trade secrecy to protect its business processes and methods, which can obscure critical financial risk exposures from regulators and the public. We develop methods for sharing and aggregating such risk exposures that protect the privacy of all parties involved and without the need for a truste...