Collaborative Research: CyberTraining: Implementation: Medium: Cross-Disciplinary Training for Joint Cyber-Physical Systems and IoT Security

协作研究：网络培训：实施：中：联合网络物理系统和物联网安全的跨学科培训

• 批准号: 2230087
• 负责人: Ahmad Taha
• 金额: $ 40.05万
• 依托单位: Vanderbilt University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2027-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2230087&HistoricalAwards=false
• 关键词: Collaborative; Research; CyberTraining; Implementation; Medium

Critical infrastructures, such as the power grid, water systems, and manufacturing plants, continue to be targeted by stealthy and debilitating cyber and physical attacks. These attacks not only hinder our national security but also jeopardize our economic prosperity. Several hurdles impede addressing the security of such critical assets, including the integration of new possibly vulnerable sensing technologies deep within such realms, in addition to the profound lack of relevant training experts from academia and both private and public sectors. Along the same line of thought, the shortage of empirical data originating from such realms, in conjunction with the complexity of such systems, further exposes the problem when facing the challenges of sophisticated state-sponsored attackers. To this end, this project serves NSF's mission to promote the progress of science by offering well-rounded training to research scientists coming from diverse related areas. The project puts forward multidisciplinary curricula in addition to catalyzing critical infrastructure training and research, while establishing active and actionable dissemination partnerships with numerous stakeholders, tangibly influencing the security of such interrelated, highly-important societal systems. The project also widely influences the training of women and minorities in these imperative cross-disciplinary areas across the US. The project uniquely curates contextualized, large-scale benign and malicious cyber and cyber-physical empirical data from real infrastructure systems to strongly enable hands-on training and research. The project then develops automated methodologies to annotate such data while indexing and sharing it with relevant research scientists to empower forward-looking research workforce development. The project also designs, delivers and integrates cross-disciplinary curricula, composed of undergraduate and graduate courses and a certificate program, dealing with evolving topics such as, physical modeling of system dynamics, related empirically driven data science applications, and joint operational security analytics. It also offers unique training opportunities with relevant private and public sector partners for both pre- and post-graduation trainees, rendered by capstone projects, internships, and competitive placement options. The project also designs and implements various security techniques, along with realistic emulation and simulation toolsets, to offer practical training expertise to researchers. The project utilizes virtualized lab setups to offer self-paced training of such developed training material, while achieving considerable outreach to relevant researchers across the US and beyond. The project fosters a community of impactful experts in the critical infrastructure security area to widely-disseminate such developed training materials and labs through coordinating and hosting yearly workshops at the collaborating institutions. The project is steered by an established program evaluation body that is composed of leading NSF Industry-University Research Partnership experts, pedagogy facilitators, and representative researchers from operational local and national training and research centers. This project is jointly funded by OAC and the CyberCorps 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.

关键的基础设施，例如电网，水系统和制造厂，继续以隐秘和使人衰弱的网络和身体攻击为目标。这些攻击不仅阻碍了我们的国家安全，而且危害了我们的经济繁荣。几个障碍阻碍了解决此类关键资产的安全性，包括将新的可能的脆弱感应技术整合到了此类领域的深处，除了严重缺乏学术界以及私营和公共部门的相关培训专家。沿着相同的思想，源自此类领域的经验数据短缺，结合了此类系统的复杂性，在面对复杂的国家赞助攻击者的挑战时进一步暴露了问题。为此，该项目通过为来自不同相关领域的研究科学家提供全面的培训来促进NSF促进科学进步的使命。该项目除了催化关键的基础设施培训和研究之外，还提供了多学科课程，同时与许多利益相关者建立了积极且可行的传播伙伴关系，从而明显地影响了这种相互关联的，非常重要的社会系统的安全性。该项目还广泛影响了在美国这些命令式跨学科地区对妇女和少数民族的培训。该项目独特地策划了从真实的基础设施系统中进行上下文化，大规模的良性和恶意网络和网络物理经验数据，以强烈实现动手培训和研究。然后，该项目开发自动化方法来注释此类数据，同时与相关的研究科学家进行索引并共享，以增强前瞻性研究人员的发展。该项目还设计，提供和集成了跨学科课程，由本科和研究生课程以及证书课程组成，并处理不断发展的主题，例如系统动态的物理建模，相关的经验驱动的数据科学应用程序以及联合运营安全分析。它还为毕业前和毕业后的学员提供了相关的私营和公共部门合作伙伴，由Capstone项目，实习和有竞争力的安置选项提供的独特培训机会。该项目还设计和实施各种安全技术，以及现实的仿真和仿真工具集，为研究人员提供实用的培训专业知识。该项目利用虚拟化的实验室设置为这种发达的培训材料提供自定进度的培训，同时向美国及其他地区的相关研究人员实现了相当大的宣传。该项目培养了关键基础设施安全区域中有影响力的专家社区，以通过协调和举办合作机构的年度研讨会来广泛降低此类开发的培训材料和实验室。该项目是由一个既定的计划评估机构都指导的，该项目由领先的NSF行业 - 大学研究伙伴关系专家，教学法促进者以及来自运营的本地和国家培训中心的代表研究人员组成。 该项目由OAC和Cyber​​corps计划共同资助。该奖项反映了NSF的法定任务，并被认为是使用基金会的知识分子优点和更广泛影响的审查标准的评估值得支持的。