DG: Secure Agency Interoperation for Effective Data Mining in Border Control and Homeland Security Applications

DG：边境管制和国土安全应用中有效数据挖掘的安全机构互操作

• 批准号: 0306838
• 负责人: Nabil Adam
• 金额: --
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-01 至 2009-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0306838&HistoricalAwards=false
• 关键词: DG; Secure; Agency; Interoperation; Effective

The objective of this grant is to address research issues related to semantic interoperability, data mining and security and authorization in the multi-agency domain of border control. Partners are the Immigration and Naturalization Agency, the Customs Service, and the Coast Guard. In addition to the research issues that will be addressed in this proposed work, the development of a proof of concept in the form of a prototype will be undertaken. Specifically, in the area of semantic interoperability, the team focuses on providing expressive common language among information sources, automatic mapping, and the ability to dynamically adapt to changing environments. Furthermore, automatic text analysis and text mining techniques will be developed to automatically, rather than manually, build the knowledge base. The team addresses some of the challenges encountered when sharing information in a secure manner, including reconciling the heterogeneity among multiple security policies, resolving semantic heterogeneity among security policies, translation of coalition level policies to implementation level and vice versa, and support of delegation in coalition based systems. Also addressed will be issues related to data mining to build an alert system. This includes developing classification/segmentation models and merging of different local models to a global model for outlier analysis, real time data mining, and providing iterative and interactive visualization. The multidisciplinary research team, which comes from multi-institutions is augmented by a set of domain experts in several related areas, including homeland security, border control, global logistics, transportation security, foreign terrorist tracking, as well as domestic and multinational investigations. These domain experts provide guidance on the functional requirements of the system and feedback on the prototype system as it progresses through its development.

该补助金的目的是解决与语义互操作性，数据挖掘和安全有关的研究问题，并在边境管制的多机构领域的授权。合作伙伴包括移民和归化局、海关和海岸警卫队。除了将在这项拟议工作中解决的研究问题外，还将以原型的形式开发概念验证。具体而言，在语义互操作性领域，该团队专注于在信息源之间提供表达性的公共语言、自动映射以及动态适应不断变化的环境的能力。此外，将开发自动文本分析和文本挖掘技术，以自动而不是人工建立知识库。该团队解决了以安全的方式共享信息时遇到的一些挑战，包括协调多个安全策略之间的异构性，解决安全策略之间的语义异构性，将联盟级别的策略转换为实现级别，反之亦然，以及支持基于联盟的系统中的委托。还将讨论与数据挖掘有关的问题，以建立一个警报系统。这包括开发分类/分割模型和将不同的局部模型合并为用于离群值分析的全局模型、真实的时间数据挖掘以及提供迭代和交互式可视化。来自多个机构的多学科研究团队由一组相关领域的专家组成，包括国土安全，边境管制，全球物流，运输安全，外国恐怖分子追踪以及国内和跨国调查。这些领域专家提供系统的功能要求的指导和反馈的原型系统，因为它通过其发展的进展。