PrePaMS: Privacy-Preserving Participant Management for Studies with Rewards

Carlos Tomé Cortiñas

Abstract

Taking part in surveys, experiments, and studies is often compensated by rewards to increase the number of participants and encourage attendance. While privacy requirements are usually considered for the actual participation, privacy aspects of the reward procedure are mostly ignored so far. To this end, we introduce PrePaMS, an efficient participation management system that supports prerequisite checks and reward procedures in a privacy- preserving way. Our system organizes participations with potential (dis-)qualifying dependencies and enables secure reward payoffs. By using a set of proven cryptographic primitives and mechanisms, participations are protected so that service providers and organizers cannot derive the identity of participants even within the reward process. We have designed and implemented a prototype of PrePaMS to show its effectiveness and evaluated its applicability in a real use case. As PrePaMS does not handle the actual participation events, it is an important and valid complement to existing solutions like web-based surveys, experiments, and studies to consistently ensure privacy in the overall process.

Date
Dec 15, 2022 1:15 PM — 2:15 PM

Felix Engelmann a Postdoc at ITU Copenhagen. His research focuses on non-interactive zero-knowledge proofs, anonymity and confidentiality, and token transaction systems.