论文标题
空间，众群数据的对抗性稳固的数据市场
An adversarially robust data-market for spatial, crowd-sourced data
论文作者
论文摘要
我们描述了一个分散数据市场的体系结构，用于激励代理商协作以众包数据的应用。该体系结构旨在奖励促进市场集体目标的数据，并将奖励公正地分配给所有贡献其数据的数据。我们证明该体系结构对Sybil，虫洞和数据中毒攻击具有弹性。为了评估体系结构的弹性，我们在汽车用例中表征了其对各种对抗威胁模型的分解点。
We describe an architecture for a decentralised data market for applications in which agents are incentivised to collaborate to crowd-source their data. The architecture is designed to reward data that furthers the market's collective goal, and distributes reward fairly to all those that contribute with their data. We show that the architecture is resilient to Sybil, wormhole, and data poisoning attacks. In order to evaluate the resilience of the architecture, we characterise its breakdown points for various adversarial threat models in an automotive use case.
