CRII: SaTC: Identifying Fraud in the Cryptocurrency Ecosystem

该项目将促进人们对网络犯罪如何能够在新兴的加密货币经济中蓬勃发展的理解。研究发现，加密货币经济中的网络犯罪，欺诈率似乎有所上升。通过了解犯罪的诱因和建立有效的监管模式，这项研究将在颠覆基于加密货币的犯罪方面取得进展。该项目将收集数据，以了解潜在的激励因素如何导致欺诈行为，以及生态系统如何使欺诈行为永久化。这项工作旨在影响加密货币的公共政策，使加密货币生态系统对消费者更安全。该项目将对这一研究领域的学生进行培训，并编写课程材料。该项目寻求纠正目前加密货币生态系统中的信息不对称，即消费者无法区分欺诈和合法企业。这个项目包括两个部分。第一部分将分析生态系统中似乎充斥着投机的一个特定部分：替代货币以及列出这些货币的相应货币交易所。双方都需要对方盈利：货币需要在交易所上市才有价值，交易所需要货币在交易所上市，以从执行交易的用户那里收取费用，以及(通常)每种货币的上市费。第二部分将广泛收集与加密货币相关的服务的社交网络数据，以了解哪些服务被诈骗的概率很高，以及哪些指标与此相关。这项工作将比较有关合法行业和欺诈的信息传播，以努力区分两者。该项目将采用纵向方法对加密货币生态系统如何演变为其当前状态进行建模，并将继续根据罪犯的适应对模型进行调整。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project will advance understanding of how cybercrime has been able to flourish in the emerging cryptocurrency economy. Research has revealed cybercrime in the cryptocurrency economy, and the rate of fraud has seemed to increase. By understanding the incentives for crime and by modeling effective regulation, this research will make progress towards upending cryptocurrency-based crime. The project will collect data towards understanding how the underlying incentives work to cause fraudulent behavior and how the ecosystem perpetuates fraud. This work aims to influence public policy on cryptocurrencies, making the cryptocurrency ecosystem safer for consumers. The project will train students in this research area and produce course materials. The project seeks to correct the information asymmetry in the current cryptocurrency ecosystem, whereby consumers cannot tell the difference between a fraud and a legitimate business. There are two parts to this project. The first part will analyze one particular sector of the ecosystem that seems to be rife with speculation: alternative currencies and the corresponding currency exchanges listing the currencies. Each needs the other to be profitable: currencies need to be listed on an exchange to be worth money, and exchanges need currencies to be listed on them to extract fees from their users executing trades and (often) listing fees for each currency. The second part will collect social network data on cryptocurrency-related services at large in order to learn which services have a high probability of being scams and what indicators are correlated with this. The work will compare the propagation of information about legitimate industries and frauds to work towards differentiating the two. The project will take a longitudinal approach towards modeling how the cryptocurrency ecosystem has evolved into its current state, and it will continue to adapt the models as criminals adapt.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.