D-ISN: TRACK 1: Collaborative Research: An Interdisciplinary Approach to Understanding, Modeling, and Disrupting Drug and Counterfeit Illicit Supply Chains
D-ISN: TRACK 1: Collaborative Research: An Interdisciplinary Approach to Understanding, Modeling, and Disrupting Drug and Counterfeit Illicit Supply Chains
批准号:
2039779
负责人:
Louise Shelley
金额:
$64.91万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-10-01 至 2025-09-30
中文摘要
这项为期五年的非法供应网络扰乱行动(D-ISN)研究的目的是了解网络世界中非法行为者在开放网络和黑暗网络中的行动,以及在线药品销售、假冒药品和包括个人防护装备(PPE)在内的商品的供应链和支付系统。它寻求通过创建工具和供应链模型来催化改变游戏规则的技术创新,以提高对非法来源产品的发现和可追溯性,并确定有效的破坏战略。这些供应链将通过洗钱利润从来源到交付进行研究。结果将由来自开放和黑暗网站的数据集以及行业合作者提供的数据来通知。该项目将提高我们国家打击网络世界和社交媒体恶意活动的能力,利用数学模型、供应链分析和计算机科学来检测和破坏药品和假冒供应链。该项目使用了一套多学科的方法,其中包括数据分析、数学建模和人种学方法,以促进我们对在线药品和假冒供应链以及如何扰乱它们的理解。特别是,这个项目将涉及打击毒品和假冒非法供应链的三个主要目标:(1)利用支付处理、托管、地下通信和法院案件的数据,从数量和质量上了解和检测非法贸易模式;(2)对供应链进行描述,然后利用适当的技术,如非合作博弈论框架,对供应链进行建模,以研究不同的破坏战略;(3)研究政府、公司和多边行为者可实施不同破坏战略的可能性。该项目将整合先进的自动数据收集和分析工具、非法贩运网络的社会学分析以及对抗性博弈理论框架。该项目团队与业界的合作以及与执法机构的讨论将促进一个互动过程,该过程可以微调破坏技术,并建议务实的现实世界实施战略和政策建议。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。
英文摘要
The objective of this five-year Disrupting Operations of Illicit Supply Networks (D-ISN) study is to understand the operations of illicit actors in the cyberworld, in both the open web and dark web, and the supply chains and payment systems for online drug sales, counterfeit pharmaceuticals, and goods, including Personal Protective Equipment (PPE). It seeks to catalyze game-changing technological innovations by creating tools and supply chain models to improve discovery and traceability of illicitly sourced products and identify effective disruption strategies. These supply chains will be studied from source to delivery through the money laundering of profits. The results will be informed by datasets drawn from open and dark websites and from data made available by industrial collaborators. The project will advance our national ability to counter malicious activities in the cyberworld and social media innovative approaches using mathematical models, supply chain analytics and computer science for the detection and disruption of drug and counterfeit supply chains. The project uses a multidisciplinary set of methods which include data analysis, mathematical modeling, and ethnographic approaches to advance our understanding of online drug and counterfeit supply chains and how to disrupt them. Specially, this project will address three major goals in combating drug and counterfeit illicit supply chains: (1) understanding and detecting the illicit trade patterns quantitatively and qualitatively by using data from the payment processing, hosting, underground communications and court cases; (2) constructing a description of the supply chain that can then be modeled using appropriate techniques such as non-cooperative game theory framework to study different disruption strategies; and (3) studying the possibility of different disruption strategies that could be implemented by government, corporate and multilateral actors. The project will integrate advanced automated data collection and analysis tools, and sociological analysis of the illicit trafficking networks, and adversarial game theory frameworks. The project team's collaboration with industry and discussions with law enforcement agencies will facilitate an interactive process that can fine-tune disruption techniques and suggest pragmatic real-world implementation strategies and policy recommendations.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.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Simulating Counterfeit Personal Protective Equipment (PPE) Supply Chains During Covid-19
模拟 Covid-19 期间的假冒个人防护装备 (PPE) 供应链
DOI:
10.1109/wsc57314.2022.10015398
发表时间:
2022
期刊:
Proceedings of the 2022 Winter Simulation Conference
影响因子:
--
作者:
[Hashemi, Layla, Jeng, Chu Chuan, Mohiuddin, Ahna, Huang, Edward, Shelley, Louise]
通讯作者:
Shelley, Louise
EAGER: ISN: A New Multi-Layered Network Approach for Improving the Detection of Human Trafficking
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批准号:1837881
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项目类别:Standard Grant
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资助金额:$29.6万
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财政年份:2018
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负责人:Louise Shelley
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依托单位:
海外基金