Data markets have the potential to foster new data-driven applications and help growing data-driven businesses. When building and deploying such markets in practice, regulations such as the European Union's General Data Protection Regulation (GDPR) impose constraints and restrictions on these markets especially when dealing with personal or privacy-sensitive data. In this paper, we present a candidate architecture for a privacy-preserving personal data market, relying on cryptographic primitives such as multi-party computation (MPC) capable of performing privacy-preserving computations on the data. Besides specifying the architecture of such a data market, we also present a privacy-risk analysis of the market following the LINDDUN methodology.

翻译：数据市场有可能促进新的数据驱动应用程序,帮助增加数据驱动企业。在实际建立和部署这类市场时,欧洲联盟一般数据保护条例等条例对这些市场施加限制和限制,特别是在处理个人或隐私敏感数据时。本文提出了个人数据保护隐私市场的候选结构,依靠多方计算等加密原始数据,能够对数据进行隐私保护计算。除了具体说明数据市场的结构外,我们还根据LINDDUN方法对市场进行隐私风险分析。