PrePaMS:用于有奖励和先决条件研究的保护隐私的参与者管理系统

Echo Meißner, Frank Kargl, Benjamin Erb, Felix Engelmann
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引用次数: 0

摘要

参与调查、实验和研究通常会得到奖励,以增加参与人数并鼓励参与。虽然参与时通常会考虑隐私要求,但奖励程序的隐私方面却大多被忽视。为此,我们引入了一个高效的参与管理系统 PrePaMS,它以保护隐私的方式支持前提条件检查和参与奖励。我们的系统可以组织具有潜在(不)资格依赖性的参与,并实现安全的奖励回报。通过利用匿名凭证和零知识证明等一系列经过验证的加密原语和机制,参与得到了保护,因此即使在奖励过程中,服务提供商和组织者也无法得知参与者的身份。在本文中,我们设计并实现了 PrePaMS 的原型,以展示其有效性,并评估了其在实际工作负载下的性能。PrePaMS 可以获取受试者是否参与过调查、实验或研究的信息。当与这些事件中实际数据收集的其他安全解决方案相结合时,PrePaMS 将成为更多隐私保护实证研究的基石。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PrePaMS: Privacy-Preserving Participant Management System for Studies with Rewards and Prerequisites
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 participation, privacy aspects of the reward procedure are mostly ignored. To this end, we introduce PrePaMS, an efficient participation management system that supports prerequisite checks and participation rewards in a privacy-preserving way. Our system organizes participations with potential (dis-)qualifying dependencies and enables secure reward payoffs. By leveraging a set of proven cryptographic primitives and mechanisms such as anonymous credentials and zero-knowledge proofs, participations are protected so that service providers and organizers cannot derive the identity of participants even within the reward process. In this paper, we have designed and implemented a prototype of PrePaMS to show its effectiveness and evaluated its performance under realistic workloads. PrePaMS covers the information whether subjects have participated in surveys, experiments, or studies. When combined with other secure solutions for the actual data collection within these events, PrePaMS can represent a cornerstone for more privacy-preserving empirical research.
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