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: 2230086
• 负责人: Elias Bou-Harb
• 金额: $ 59.95万
• 依托单位: University of Texas at San Antonio
• 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 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2230086&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.

关键基础设施，如电网，供水系统和制造工厂，继续成为隐形和削弱网络和物理攻击的目标。这些攻击不仅妨碍我们的国家安全，而且危及我们的经济繁荣。有几个障碍阻碍解决这些关键资产的安全问题，包括将新的可能脆弱的传感技术深入这些领域，以及严重缺乏来自学术界和私营部门和公共部门的相关培训专家。沿着同样的思路，缺乏来自这些领域的经验数据，加上这些系统的复杂性，在面对复杂的国家支持的攻击者的挑战时，进一步暴露了问题。为此，该项目服务于NSF的使命，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科学的进步。该项目提出了多学科课程，促进关键基础设施的培训和研究，同时与众多利益攸关方建立积极和可操作的传播伙伴关系，切实影响这些相互关联的高度重要的社会系统的安全。该项目还广泛影响了美国各地妇女和少数民族在这些必要的跨学科领域的培训。该项目以独特的方式从真实的基础设施系统中收集大规模良性和恶意网络和网络物理经验数据，以大力支持实践培训和研究。然后，该项目开发自动化方法来注释这些数据，同时将其编入索引并与相关研究科学家共享，以增强前瞻性研究人员的发展能力。该项目还设计，提供和集成跨学科课程，包括本科和研究生课程以及证书课程，处理不断发展的主题，如系统动力学的物理建模，相关的经验驱动的数据科学应用程序和联合运营安全分析。它还为毕业前和毕业后的学员提供与相关私营和公共部门合作伙伴的独特培训机会，通过顶点项目，实习和竞争性就业选择提供。该项目还设计和实施各种安全技术，沿着逼真的仿真和模拟工具集，为研究人员提供实用的培训专业知识。该项目利用虚拟化实验室设置，为此类开发的培训材料提供自定进度的培训，同时与美国及其他地区的相关研究人员进行了相当大的接触。该项目通过在合作机构协调和主办年度讲习班，培养了一个重要基础设施安全领域有影响力的专家社区，以广泛传播这种开发的培训材料和实验室。该项目由一个既定的计划评估机构指导，该机构由领先的NSF行业-大学研究合作伙伴关系专家，教学促进者以及来自当地和国家培训和研究中心的代表性研究人员组成。 该项目由OAC和CyberCorps计划共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。