CyberTraining: Implementation: Small: Infrastructure Cybersecurity Curriculum Development and Training for Advanced Manufacturing Research Workforce
CyberTraining: Implementation: Small: Infrastructure Cybersecurity Curriculum Development and Training for Advanced Manufacturing Research Workforce
批准号:
2230025
负责人:
Wenyao Xu
金额:
$50.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-01-01 至 2025-12-31
中文摘要
该项目旨在为本科生,研究生和CI专业人员举办为期10周的暑期课程,以解决先进制造业和工业4.0中的网络基础设施(CI)需求问题。该项目开发了教学材料,并实施了一个新的CyberTrainng项目,以培训当前和未来的先进制造(AM)研究人员在CI网络安全方面的能力。它使参与者面临工业4.0中以CI为中心的网络安全的各种挑战,重点是国家对训练有素和知识渊博的AM研究人员的重要需求,他们能够解决新兴复杂工业4.0制造系统中的现实网络安全问题。培训还包括在AM中安全采用以CI为中心的计算工具。该项目通过培训研究人员来应对工业4.0中以CI为中心的网络安全挑战,对公共和私营部门产生了直接和长期的影响。布法罗大学(UB)在以AM和CI为中心的研究领域建立了坚实的和智力参与的计划。该项目可以为AM研究人员形成一个新的协同研究和教育计划。此外,利用与UB和当地工业合作伙伴建立的多样性促进计划的合作,这个网络培训项目可以显着增加项目的集体影响,该项目的目标是弥合一般网络安全教育与以CI为中心的先进制造研究之间的差距,培训并准备一批未来的AM研究人员,他们拥有先进的CI网络安全知识,可以在未来的职业生涯中担任特定的角色。目前,随着计算机,网络和智能设备渗透到工业4.0的各个方面,CI网络安全培训的需求很高,以涵盖深入融入现代CI为中心的制造环境的学科为导向的主题,超越计算机/网络安全的核心素养。具体来说,该团队旨在开发和提供一个创新的培训计划,包括一套动手实验室,介绍特定领域的网络安全攻击表面和缓解技术。培训技能对于解决AM硬件中工业4.0系统的各种网络安全挑战至关重要(例如,工业控制器和电力线),AM软件(例如,嵌入式固件、CAD/CAM软件以及监控和数据采集(SCADA)系统),AM通信网络(例如,工业物联网,CAN总线)和其他关键CI组件(例如,新的边渠道发现、IP盗窃/保护、质量控制工具、供应链软件/数据库和事件响应策略)。此外,该项目采用学习科学原则,特别是主动学习和基于探究的学习策略,促进学生的学习成果,并为教师提供形成性反馈。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智力价值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
This project addresses the problem of Cyberinfrastructure (CI) needs in Advanced Manufacturing and Industry 4.0 by aiming to host a 10-week summer program for undergraduate, graduate students and CI professionals. The project develops instructional materials and implements a new CyberTrainng project to train current and future Advanced Manufacturing (AM) research workforce members in CI cybersecurity. It exposes the participants to various challenges of CI centered cybersecurity in Industry 4.0, with a focus on the vital national need for well trained and highly knowledgeable AM researchers who are capable of solving real-world cybersecurity problems in emerging complex Industry 4.0 manufacturing systems. The training also includes the secure and safe adoption of CI centered computational tools in AM. The project has direct and long term impacts in both the public and private sectors by training the research workforce to address CI centered cybersecurity challenges in Industry 4.0. University at Buffalo (UB) has established solid and intellectually-engaging programs in the areas of AM and CI centered research areas. This project can form a new synergetic research and education program for the AM research workforce. Moreover, utilizing the collaboration with established diversity-promotion programs at UB and local industrial partners, this CyberTraining project can significantly increase the collective impact of the project, benefiting numerous graduate and undergraduate students from underrepresented groups and improving the diversity of the research workforce.The goal of this project is to bridge the gap between general cybersecurity education and CI centered Advanced Manufacturing research training and to prepare a group of future AM research workforce with advanced CI cybersecurity knowledge to undertake specific roles in their future careers. Currently, as computers,networks and intelligent devices penetrating every aspect of Industry 4.0, CI cybersecurity training is in high demand to cover materials that deeply incorporate discipline-oriented topics for modern CI-centered manufacturing environments beyond core literacy in computers/networks security. Specifically, the team aims to develop and provide an innovative training program, including a set of hands-on labs that introduce domain specific cybersecurity attack surfaces and mitigation techniques. The training skills are crucial to address the various cybersecurity challenges of Industry 4.0 systems in AM hardware (e.g., industrial controllers and power line), AM software (e.g., embedded firmware, CAD/CAM software, and supervisory control and data acquisition (SCADA) systems), AM communication networks (e.g., industrial IoTs, CAN bus) and other crucial CI components (e.g., new side channel discovery, IP theft/protection, quality control tools, supply chain software/database, and incident response strategies). Moreover, the project employs learning science principles, specifically the active learning and inquiry based learning strategies, that facilitate students' learning outcomes and provide formative feedback to instructors.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.
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