The business value of privacy-preserving technologies: the case of multiparty computation in the telecom industry

Purpose: This paper aims to propose a framework for how privacy-preserving technologies (PETs) create business value for organizations. The framework was developed by examining the literature on privacy and information technology’s impact (symbolic and function). The authors evaluate the framework’s applicability using multiparty computation ...

Multiparty Computation: Identifying the Consumers’ Willingness to Share Sensitive Automotive Data on MPC-­enabled Data Marketplaces: A Discrete Choice Modelling Approach

Over the last several years, the volume of data generated by the Internet of Things (IoT) has expanded at a rapid pace around the world. These often very detailed sensor data could be utilized by many different parties in order to improve services. This same tendency is seen in the automotive sector, where lots of data are gathered by newer and...

Secure MPC-Sortition: Consolidating Innovations in Democracy and Cryptography

Globally, citizens’ assemblies have been gaining momentum as a way to counter dissatisfaction in democracies. Central to the citizens’ assembly is sortition, the process of randomly selecting political representatives given certain demographic criteria. In order to have an assembly representative of the population, personal data is necessary to...

Cleaning Up Our Financial System: Combating Money Laundering Using Multiparty Computation

Globally, it is estimated by the UN that 2% - 5% of the annual GDP is lost to money laundering. Cur-rent anti-money laundering efforts are hindered by both the lack of trust between financial institutions internationally and the presence of local privacy regulations like GDPR. This makes it unfeasible to share plain transaction data between...

Privacy-Preserving Distributed Processing: Metrics, Bounds and Algorithms

Privacy-preserving distributed processing has recently attracted considerable attention. It aims to design solutions for conducting signal processing tasks over networks in a decentralized fashion without violating privacy. Many existing algorithms can be adopted to solve this problem such as differential privacy, secure multiparty...

Multiparty Computation: The effect of multiparty computation on firms' willingness to contribute protected data

Organizations share data for collective purposes: new opportunities are created to allow business enhancement. While new businesses contribute to economic development, valid reasons exist to inhibit data sharing (e.g. citizen privacy and sensitive information). Multi Party computation (MPC) provides a solution to these risks. However, MPC...