D-ISN: TRACK 2: Building a Community to Use Intelligence from Online Underground Markets

在传统市场和在线暗网市场中，非法商业都依赖于供应链，其方式与合法商业大致相同。供应链协调定义市场的生产、销售、信息和资金流。然而，尽管人们对了解毒品、武器和假冒商品的非法供应链投入了广泛的研究注意力，但此前还没有研究对虚拟商品非法供应链上不同行为者之间的相互作用进行实证调查，以及这一供应链对不同事件的灵活性和适应性，如执法干预、健康危机和竞争对手的努力。此外，尽管有很强的理由相信信用卡和个人识别码等虚拟商品可能在伪造证件的过程中发挥重要作用，但以往的研究并未广泛关注识别这两个相关供应链的潜在重叠。非法供应网络扰乱行动(D-ISN)计划赠款旨在利用该小组在信息流、银行、数据收集和分析方面的书面专业知识，以及来自几个科学学科(例如犯罪学、政治学和经济学)的理论观点，以更好地了解虚拟商品、假币和假文件的非法供应链，它们之间的相互作用，以及应在哪些节点实施颠覆性努力，以努力摧毁这些网络。这一规划项目将探索颠覆性战略对供应链沿线不同行为者活动的实地经验影响的有效性，并将支持开发机器学习模型和工具，以支持两个供应链沿线行为者的潜在可追溯性。此外，该项目将为学术、行业和执法机构提供低成本但强大的工具，以打击在线虚拟商品、假币和假文件行为者的非法供应链。该项目将通过建立一个包括学术界、行业和执法部门成员在内的当地研究社区来实现其目标，这些成员拥有独特的专业知识组合，将导致对犯罪市场进行有效、道德和法律干预。该小组将首先主办工作组会议和会议。根据这些会议的结果，该小组将设计和部署试验性研究，以开发适当的工具来收集和分析来自外地的数据。将利用进一步的会议和工作组会议来完善这些工具及其实施。收集的数据将有助于更好地了解支持虚拟产品(例如信用卡、在线身份)、假币和欺诈性文件地下市场的供应链的线上和线下维度。这些努力应该产生经验证据、专家洞察力和坚实的机构关系，从而支持未来与D-ISN计划一致的高影响力项目的发展。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。

Illicit commerce, in both conventional markets and online darknet markets, relies on a supply chain in much the same way as licit commerce. The supply chain coordinates the production, sales, information and capital flows that define the markets. However, while extensive research attention has been devoted to understanding the illicit supply chains of drugs, arms, and counterfeit commodities, no previous study has empirically investigated the interactions between different actors on the illicit supply chain of virtual goods, and the flexibility and adaptability of this supply chain to different events like law enforcement interventions, health crises, and rival group’s efforts. Moreover, although there are strong reasons to believe that virtual goods such as credit cards and individual personal identifiers may play an important role in the production of fake documents, previous research has not paid extensive attention to identification of potential overlap of these two related supply chains. This Disrupting Operations of Illicit Supply Networks (D-ISN) planning grant seeks to leverage the team's documented expertise in the flow of information, banking, data gathering and analysis, and theoretical perspectives drawn from several scientific disciplines (for example, criminology, political science, and economics) to generate a better understanding of the illicit supply chains of virtual goods, counterfeit money and fake documents, the interaction between them, and the junctions in which disruptive efforts should be implemented in effort to dismantle these networks. This planning project will explore the effectiveness of disruptive strategies in impacting the activities of different actors along the supply chains empirically in the field, and will support the development of machine learning models and tools that support the potential traceability of actors along the two supply chains. Moreover, the project will generate low-cost but powerful tools for academic, industry, and law enforcement agencies to counter the efforts of illicit supply chains of online virtual goods, counterfeit money and fake documents actors.This project will achieve its goals by building a local research community that includes members of academia, industry, and law enforcement who possess a unique combination of expertise and which will result in effective, ethical, and legal interventions in the criminal markets. The team will first host working group meetings and conferences. Based on the outcomes of these meetings, the team will design and deploy pilot studies to work on the development of appropriate tools for collecting and analyzing data from the field. Further meetings and workgroup meetings will be used to refine the tools and their implementation. The data collected will allow better understanding the online and offline dimension of the supply chain supporting the underground markets of virtual products (for example credit cards, online identities), counterfeit currency and fraudulent documents. These efforts should result in empirical evidence, expert insights and solid institutional relationships which could support the development of a future high impact project which is consistent with the D-ISN program.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.